Abstract:

Efficient sequence specific gene silencing is possible through the use of
siRNA technology. By selecting particular siRNAs by rational design, one
can maximize the generation of an effective gene silencing reagent, as
well as methods for silencing genes. Methods, compositions, and kits
generated through rational design of siRNAs are disclosed including those
directed to nucleotide sequences for BACE.

Claims:

1. An siRNA molecule, wherein said siRNA molecule consists of: (a) a
duplex region; and (b) either no overhang regions or at least one
overhang region, wherein each overhang region contains six or fewer
nucleotides, wherein the duplex region consists of a sense region and an
antisense region, wherein said sense region and said antisense region
together form said duplex region and said duplex region is 19-30 base
pairs in length and said antisense region comprises a sequence that is
the complement of a sequence selected from SEQ ID NOs: 438-532, 534-542
and 544-734.

2. The siRNA molecule of claim 1, wherein said antisense region and said
sense region are each 19-25 bases in length.

3. The siRNA molecule of claim 2, wherein said antisense region and said
sense region are each 19 bases in length.

4. The siRNA molecule of claim 1, wherein said siRNA molecule has at least
one overhang region.

5. The siRNA molecule of claim 1, wherein said siRNA molecule has no
overhang regions.

6. The siRNA molecule of claim 2, wherein said siRNA molecule has at least
one overhang region.

7. The siRNA molecule of claim 2, wherein said siRNA molecule has no
overhang regions.

8. The siRNA molecule of claim 3, wherein said siRNA molecule has at least
one overhang region.

9. The siRNA molecule of claim 3, wherein said siRNA molecule has no
overhang regions.

10. A chemically synthesized double stranded siRNA molecule, wherein:(a)
each strand of said double stranded siRNA molecule is between 19 and 30
nucleotides in length; and(b) one strand of said siRNA molecule comprises
a sequence that is the complement of a sequence selected from SEQ ID NOs:
438-532, 534-542 and 544-734.

11. The chemically synthesized double stranded siRNA molecule of claim 20,
wherein each strand of said siRNA molecule is 19 nucleotides in length.

12. A pool of at least two siRNAs, wherein said pool comprises a first
siRNA and a second siRNA, wherein said first siRNA is the siRNA molecule
of claim 1, wherein the duplex region of said first siRNA is a first
duplex region and said second siRNA consists of a second duplex region
and either no overhang regions or at least one overhang region, wherein
each overhang region contains six or fewer nucleotides, wherein the
second duplex region of said second siRNA comprises a sense region and an
antisense region, wherein said sense region and said antisense region of
said second siRNA together form said second duplex region and said second
duplex region is 19-30 base pairs in length and said antisense region of
said second duplex region comprises a sequence that is the complement of
a sequence selected from the group consisting of a sequence selected from
SEQ ID NOs: 438-532, 534-542 and 544-734.

13. The pool of claim 12, wherein said first siRNA and said second siRNA
each have no overhang regions.

14. The pool of claim 12, wherein said first duplex region and said second
duplex region are each 19-25 base pairs in length.

15. The pool of claim 14, wherein said first duplex region and said second
duplex region are each 19 base pairs in length.

16. The pool of claim 15, wherein said first duplex region contains no
overhang regions.

17. The pool of claim 15, wherein the second duplex region contains no
overhang regions.

18. The pool of claim 15, wherein the first duplex region contains at
least one overhang region.

19. The pool of claim 15, wherein the second duplex region contains at
least one overhang region.

20. The chemically synthesized double stranded siRNA molecule of claim 10
wherein each strand of said siRNA molecule is 19-25 nucleotides in
length.

Description:

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001]This application is a divisional application of U.S. Ser. No.
11/978,457, filed Oct. 29, 2007, which is a continuation-in-part of U.S.
Ser. No. 10/714,333, filed Nov. 14, 2003, which claims the benefit of
U.S. Provisional Application No. 60/426,137, filed Nov. 14, 2002, and
also claims the benefit of U.S. Provisional Application No. 60/502,050,
filed Sep. 10, 2003; U.S. Ser. No. 11/978,457 is also a
continuation-in-part of U.S. Ser. No. 10/940,892, filed Sep. 14, 2004,
which is a continuation of PCT Application No. PCT/US 04/14885,
international filing date May 12, 2004. The disclosures of the priority
applications, including the sequence listings and tables submitted in
electronic form in lieu of paper, are incorporated by reference into the
instant specification.

SEQUENCE LISTING

[0002]The sequence listing for this application has been submitted in
accordance with 37 CFR §1.52(e) and 37 CFR §1.821 on CD-ROM in
lieu of paper on a disk containing the sequence listing file entitled
"DHARMA--2100-US132_CRF.txt" created Dec. 8, 2009, 128 kb.
Applicants hereby incorporate by reference the sequence listing provided
on CD-ROM in lieu of paper into the instant specification.

FIELD OF INVENTION

[0003]The present invention relates to RNA interference ("RNAi").

BACKGROUND OF THE INVENTION

[0004]Relatively recently, researchers observed that double stranded RNA
("dsRNA") could be used to inhibit protein expression. This ability to
silence a gene has broad potential for treating human diseases, and many
researchers and commercial entities are currently investing considerable
resources in developing therapies based on this technology.

[0006]It is generally considered that the major mechanism of RNA induced
silencing (RNA interference, or RNAi) in mammalian cells is mRNA
degradation. Initial attempts to use RNAi in mammalian cells focused on
the use of long strands of dsRNA. However, these attempts to induce RNAi
met with limited success, due in part to the induction of the interferon
response, which results in a general, as opposed to a target-specific,
inhibition of protein synthesis. Thus, long dsRNA is not a viable option
for RNAi in mammalian systems.

[0007]More recently it has been shown that when short (18-30 bp) RNA
duplexes are introduced into mammalian cells in culture,
sequence-specific inhibition of target mRNA can be realized without
inducing an interferon response. Certain of these short dsRNAs, referred
to as small inhibitory RNAs ("siRNAs"), can act catalytically at
sub-molar concentrations to cleave greater than 95% of the target mRNA in
the cell. A description of the mechanisms for siRNA activity, as well as
some of its applications are described in Provost et al. (2002)
Ribonuclease Activity and RNA Binding of Recombinant Human Dicer, EMBO J.
21(21): 5864-5874; Tabara et al. (2002) The dsRNA Binding Protein RDE-4
Interacts with RDE-1, DCR-1 and a DexH-box Helicase to Direct RNAi in C.
elegans, Cell 109(7):861-71; Ketting et al. (2002) Dicer Functions in RNA
Interference and in Synthesis of Small RNA Involved in Developmental
Timing in C. elegans; Martinez et al., Single-Stranded Antisense siRNAs
Guide Target RNA Cleavage in RNAi, Cell 110(5):563; Hutvagner & Zamore
(2002) A microRNA in a multiple-turnover RNAi enzyme complex, Science
297:2056.

[0008]From a mechanistic perspective, introduction of long double stranded
RNA into plants and invertebrate cells is broken down into siRNA by a
Type III endonuclease known as Dicer. Sharp, RNA interference--2001,
Genes Dev. 2001, 15:485. Dicer, a ribonuclease-III-like enzyme, processes
the dsRNA into 19-23 base pair short interfering RNAs with characteristic
two base 3' overhangs. Bernstein, Caudy, Hammond, & Hannon (2001) Role
for a bidentate ribonuclease in the initiation step of RNA interference,
Nature 409:363. The siRNAs are then incorporated into an RNA-induced
silencing complex (RISC) where one or more helicases unwind the siRNA
duplex, enabling the complementary antisense strand to guide target
recognition. Nykanen, Haley, & Zamore (2001) ATP requirements and small
interfering RNA structure in the RNA interference pathway, Cell 107:309.
Upon binding to the appropriate target mRNA, one or more endonucleases
within the RISC cleaves the target to induce silencing. Elbashir,
Lendeckel, & Tuschl (2001) RNA interference is mediated by 21- and
22-nucleotide RNAs, Genes Dev. 15:188, FIG. 1.

[0009]The interference effect can be long lasting and may be detectable
after many cell divisions. Moreover, RNAi exhibits sequence specificity.
Kisielow, M. et al. (2002) Isoform-specific knockdown and expression of
adaptor protein ShcA using small interfering RNA, J. Biochem. 363:1-5.
Thus, the RNAi machinery can specifically knock down one type of
transcript, while not affecting closely related mRNA. These properties
make siRNA a potentially valuable tool for inhibiting gene expression and
studying gene function and drug target validation. Moreover, siRNAs are
potentially useful as therapeutic agents against: (1) diseases that are
caused by over-expression or misexpression of genes; and (2) diseases
brought about by expression of genes that contain mutations.

[0010]Successful siRNA-dependent gene silencing depends on a number of
factors. One of the most contentious issues in RNAi is the question of
the necessity of siRNA design, i.e., considering the sequence of the
siRNA used. Early work in C. elegans and plants circumvented the issue of
design by introducing long dsRNA (see, for instance, Fire, A. et al.
(1998) Nature 391:806-811). In this primitive organism, long dsRNA
molecules are cleaved into siRNA by Dicer, thus generating a diverse
population of duplexes that can potentially cover the entire transcript.
While some fraction of these molecules are non-functional (i.e., induce
little or no silencing) one or more have the potential to be highly
functional, thereby silencing the gene of interest and alleviating the
need for siRNA design. Unfortunately, due to the interferon response,
this same approach is unavailable for mammalian systems. While this
effect can be circumvented by bypassing the Dicer cleavage step and
directly introducing siRNA, this tactic carries with it the risk that the
chosen siRNA sequence may be non-functional or semi-functional.

[0011]A number of researches have expressed the view that siRNA design is
not a crucial element of RNAi. On the other hand, others in the field
have begun to explore the possibility that RNAi can be made more
efficient by paying attention to the design of the siRNA. Unfortunately,
none of the reported methods have provided a satisfactory scheme for
reliably selecting siRNA with acceptable levels of functionality.
Accordingly, there is a need to develop rational criteria by which to
select siRNA with an acceptable level of functionality, and to identify
siRNA that have this improved level of functionality, as well as to
identify siRNAs that are hyperfunctional.

[0013]According to a first embodiment, the present invention provides a
kit for gene silencing, wherein said kit is comprised of a pool of at
least two siRNA duplexes, each of which is comprised of a sequence that
is complementary to a portion of the sequence of one or more target
messenger RNA, and each of which is selected using non-target specific
criteria.

[0014]According to a second embodiment, the present invention provides a
method for selecting an siRNA, said method comprising applying selection
criteria to a set of potential siRNA that comprise 18-30 base pairs,
wherein said selection criteria are non-target specific criteria, and
said set comprises at least two siRNAs and each of said at least two
siRNAs contains a sequence that is at least substantially complementary
to a target gene; and determining the relative functionality of the at
least two siRNAs.

[0015]According to a third embodiment, the present invention also provides
a method for selecting an siRNA wherein said selection criteria are
embodied in a formula comprising:

(-8)*A1+(-1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(-4)*A9+(-5)-
*A10+(-2)*A11+(-5)*A12+(17)*A13+(-3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+-
(30)*A19+(-13)*U1+(-10)*U2+(2)*U3+(-2)*U4+(-5)*U5+(5)*U6+(-2)*U7+(-10)*U8+-
(-5)*U9+(15)*U10+(-1)*U11+(0)*U12+(10)*U13+(-9)*U14+(-13)*U15+(-10)*U16+(3-
)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(-21)*C3+(5)*C4+(-9)*C5+(-20)*C6+(-18)-
*C7+(-5)*C8+(5)*C9+(1)*C10+(2)*C11+(-5)*C12+(-3)*C13+(-6)*C14+(-2)*C15+(-5-
)*C16+(-3)*C17+(-12)*C18+(-18)*C19+(14)*G1+(8)*G2+(7)*G3+(-10)*G4+(-4)*G5+-
(2)*G6+(1)*G7+(9)*G8+(5)*G9+(-11)*G10+(1)*G11+(9)*G12+(-24)*G13+(18)*G14+(-
11)*G15+(13)*G16+(-7)*G17+(-9)*G18+(-22)*G19+6*(number of A+U in position
15-19)-3*(number of G+C in whole siRNA), Formula X [0016]wherein
position numbering begins at the 5'-most position of a sense strand, and
[0017]A1=1 if A is the base at position 1 of the sense strand,
otherwise its value is 0; [0018]A2=1 if A is the base at position 2
of the sense strand, otherwise its value is 0; [0019]A3=1 if A is
the base at position 3 of the sense strand, otherwise its value is 0;
[0020]A4=1 if A is the base at position 4 of the sense strand,
otherwise its value is 0; [0021]A5=1 if A is the base at position 5
of the sense strand, otherwise its value is 0; [0022]A6=1 if A is
the base at position 6 of the sense strand, otherwise its value is 0;
[0023]A7=1 if A is the base at position 7 of the sense strand,
otherwise its value is 0; [0024]A10=1 if A is the base at position
10 of the sense strand, otherwise its value is 0; [0025]A11=1 if A
is the base at position 11 of the sense strand, otherwise its value is 0;
[0026]A13=1 if A is the base at position 13 of the sense strand,
otherwise its value is 0; [0027]A19=1 if A is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0028]C3=1
if C is the base at position 3 of the sense strand, otherwise its value
is 0; [0029]C4=1 if C is the base at position 4 of the sense strand,
otherwise its value is 0; [0030]C5=1 if C is the base at position 5
of the sense strand, otherwise its value is 0; [0031]C6=1 if C is
the base at position 6 of the sense strand, otherwise its value is 0;
[0032]C7=1 if C is the base at position 7 of the sense strand,
otherwise its value is 0; [0033]C9=1 if C is the base at position 9
of the sense strand, otherwise its value is 0; [0034]C17=1 if C is
the base at position 17 of the sense strand, otherwise its value is 0;
[0035]C18=1 if C is the base at position 18 of the sense strand,
otherwise its value is 0; [0036]C19=1 if C is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0037]G1=1
if G is the base at position 1 on the sense strand, otherwise its value
is 0; [0038]G2=1 if G is the base at position 2 of the sense strand,
otherwise its value is 0; [0039]G8=1 if G is the base at position 8
on the sense strand, otherwise its value is 0; [0040]G10=1 if G is
the base at position 10 on the sense strand, otherwise its value is 0;
[0041]G13=1 if G is the base at position 13 on the sense strand,
otherwise its value is 0; [0042]G19=1 if G is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0043]U1=1
if U is the base at position 1 on the sense strand, otherwise its value
is 0; [0044]U2=1 if U is the base at position 2 on the sense strand,
otherwise its value is 0; [0045]U3=1 if U is the base at position 3
on the sense strand, otherwise its value is 0; [0046]U4=1 if U is
the base at position 4 on the sense strand, otherwise its value is 0;
[0047]U7=1 if U is the base at position 7 on the sense strand,
otherwise its value is 0; [0048]U9=1 if U is the base at position 9
on the sense strand, otherwise its value is 0; [0049]U10=1 if U is
the base at position 10 on the sense strand, otherwise its value is 0;
[0050]U15=1 if U is the base at position 15 on the sense strand,
otherwise its value is 0; [0051]U16=1 if U is the base at position
16 on the sense strand, otherwise its value is 0; [0052]U17=1 if U
is the base at position 17 on the sense strand, otherwise its value is 0;
[0053]U18=1 if U is the base at position 18 on the sense strand,
otherwise its value is 0. [0054]GC15 -19=the number of G and C bases
within positions 15-19 of the sense strand, or within positions 15-18 if
the sense strand is only 18 base pairs in length; [0055]GCtotal=the
number of G and C bases in the sense strand; [0056]Tm=100 if the siRNA
oligo has the internal repeat longer then 4 base pairs, otherwise its
value is 0; and [0057]X=the number of times that the same nucleotide
repeats four or more times in a row.

[0058]According to a fourth embodiment, the invention provides a method
for developing an algorithm for selecting siRNA, said method comprising:
(a) selecting a set of siRNA; (b) measuring gene silencing ability of
each siRNA from said set; (c) determining relative functionality of each
siRNA; (d) determining improved functionality by the presence or absence
of at least one variable selected from the group consisting of the
presence or absence of a particular nucleotide at a particular position,
the total number of As and Us in positions 15-19, the number of times
that the same nucleotide repeats within a given sequence, and the total
number of Gs and Cs; and (e) developing an algorithm using the
information of step (d).

[0059]According to a fifth embodiment, the present invention provides a
kit, wherein said kit is comprised of at least two siRNAs, wherein said
at least two siRNAs comprise a first optimized siRNA and a second
optimized siRNA, wherein said first optimized siRNA and said second
optimized siRNA are optimized according a formula comprising Formula X.

[0060]The present invention also provides a method for identifying a
hyperfunctional siRNA, comprising applying selection criteria to a set of
potential siRNA that comprise 18-30 base pairs, wherein said selection
criteria are non-target specific criteria, and said set comprises at
least two siRNAs and each of said at least two siRNAs contains a sequence
that is at least substantially complementary to a target gene;
determining the relative functionality of the at least two siRNAs and
assigning each of the at least two siRNAs a functionality score; and
selecting siRNAs from the at least two siRNAs that have a functionality
score that reflects greater than 80 percent silencing at a concentration
in the picomolar range, wherein said greater than 80 percent silencing
endures for greater than 120 hours.

[0061]According to a sixth embodiment, the present invention provides a
hyperfunctional siRNA that is capable of silencing Bcl2.

[0062]According to a seventh embodiment, the present invention provides a
method for developing an siRNA algorithm for selecting functional and
hyperfunctional siRNAs for a given sequence. The method comprises:

[0063](a) selecting a set of siRNAs;

[0064](b) measuring the gene silencing ability of each siRNA from said
set;

[0065](c) determining the relative functionality of each siRNA;

[0066](d) determining the amount of improved functionality by the presence
or absence of at least one variable selected from the group consisting of
the total GC content, melting temperature of the siRNA, GC content at
positions 15-19, the presence or absence of a particular nucleotide at a
particular position, relative thermodynamic stability at particular
positions in a duplex, and the number of times that the same nucleotide
repeats within a given sequence; and

[0067](e) developing an algorithm using the information of step (d).

[0068]According to this embodiment, preferably the set of siRNAs comprises
at least 90 siRNAs from at least one gene, more preferably at least 180
siRNAs from at least two different genes, and most preferably at least
270 and 360 siRNAs from at least three and four different genes,
respectively. Additionally, in step (d) the determination is made with
preferably at least two, more preferably at least three, even more
preferably at least four, and most preferably all of the variables. The
resulting algorithm is not target sequence specific.

[0069]In another embodiment, the present invention provides rationally
designed siRNAs identified using the formulas above.

[0070]In yet another embodiment, the present invention is directed to
hyperfunctional siRNA.

[0071]The ability to use the above algorithms, which are not sequence or
species specific, allows for the cost-effective selection of optimized
siRNAs for specific target sequences. Accordingly, there will be both
greater efficiency and reliability in the use of siRNA technologies.

[0072]In various embodiments, siRNAs that target nucleotide sequences for
beta secretase (BACE) are provided. In various embodiments, the siRNAs
are rationally designed. In various embodiments, the siRNAs are
functional or hyperfunctional.

[0073]In various embodiments, an siRNA that targets the nucleotide
sequence for BACE is provided, wherein the siRNA is selected from the
group consisting of various siRNA sequences targeting the nucleotide
sequences for BACE that are disclosed herein. In various embodiments, the
siRNA sequence is selected from the group consisting of SEQ ID NO. 438.to
SEQ ID NO. 734.

[0074]In various embodiments, siRNA comprising a sense region and an
antisense region are provided, said sense region and said antisense
region together form a duplex region comprising 18-30 base pairs, and
said sense region comprises a sequence that is at least 90% similar to a
sequence selected from the group consisting of siRNA sequences targeting
nucleotide sequences for BACE that are disclosed herein. In various
embodiments, the siRNA sequence is selected from the group consisting of
SEQ ID NO. 438 to SEQ ID NO. 734.

[0075]In various embodiments, an siRNA comprising a sense region and an
antisense region is provided, said sense region and said antisense region
together form a duplex region comprising 18-30 base pairs, and said sense
region comprises a sequence that is identical to a contiguous stretch of
at least 18 bases of a sequence selected from the group consisting of SEQ
ID NO. 438 to SEQ ID NO. 734. In various embodiments, the duplex region
is 19-30 base pairs, and the sense region comprises a sequence that is
identical to a sequence selected from the group consisting of SEQ ID NO.
438 to SEQ ID NO. 734.

[0076]In various embodiments, a pool of at least two siRNAs is provided,
wherein said pool comprises a first siRNA and a second siRNA, said first
siRNA comprising a duplex region of length 18-30 base pairs that has a
first sense region that is at least 90% similar to 18 bases of a first
sequence selected from the group consisting of SEQ ID NO. 438 to SEQ ID
NO. 734, and said second siRNA comprises a duplex region of length 18-30
base pairs that has a second sense region that is at least 90% similar to
18 bases of a second sequence selected from the group consisting of SEQ
ID NO. 438 to SEQ ID NO. 734, wherein said first sense region and said
second sense region are not identical.

[0077]In various embodiments, the first sense region comprises a sequence
that is identical to at least 18 bases of a sequence selected from the
group consisting of SEQ ID NO. 438 to SEQ ID NO. 734, and said second
sense region comprises a sequence that is identical to at least 18 bases
of a sequence selected from the group consisting of SEQ ID NO. 438 to SEQ
ID NO. 734. In various embodiments, the duplex of said first siRNA is
19-30 base pairs, and said first sense region comprises a sequence that
is at least 90% similar to a sequence selected from the group consisting
of SEQ ID NO. 438 to SEQ ID NO. 734, and said duplex of said second siRNA
is 19-30 base pairs and comprises a sequence that is at least 90% similar
to a sequence selected from the group consisting of SEQ ID NO. 438 to SEQ
ID NO. 734.

[0078]In various embodiments, the duplex of said first siRNA is 19-30 base
pairs and said first sense region comprises a sequence that is identical
to at least 18 bases of a sequence selected from the group consisting of
SEQ ID NO. 438 to SEQ ID NO. 734, and said duplex of said second siRNA is
19-30 base pairs and said second region comprises a sequence that is
identical to a sequence selected from the group consisting of SEQ ID NO.
438 to SEQ ID NO. 734.

[0079]For a better understanding of the present invention together with
other and further advantages and embodiments, reference is made to the
following description taken in conjunction with the examples, the scope
of which is set forth in the appended claims.

BRIEF DESCRIPTION OF THE FIGURES

[0080]FIG. 1 shows a model for siRNA-RISC interactions. RISC has the
ability to interact with either end of the siRNA or miRNA molecule.
Following binding, the duplex is unwound, and the relevant target is
identified, cleaved, and released.

[0081]FIG. 2 is a representation of the functionality of two hundred and
seventy siRNA duplexes that were generated to target human cyclophilin,
human diazepam-binding inhibitor (DB), and firefly luciferase.

[0082]FIG. 3a is a representation of the silencing effect of 30 siRNAs in
three different cells lines, HEK293, DU145, and Hela. FIG. 3b shows the
frequency of different functional groups (>95% silencing (black),
>80% silencing (gray), >50% silencing (dark gray), and <50%
silencing (white)) based on GC content. In cases where a given bar is
absent from a particular GC percentage, no siRNA were identified for that
particular group. FIG. 3c shows the frequency of different functional
groups based on melting temperature (Tm).

[0083]FIG. 4 is a representation of a statistical analysis that revealed
correlations between silencing and five sequence-related properties of
siRNA: (A) an A at position 19 of the sense strand, (B) an A at position
3 of the sense strand, (C) a U at position 10 of the sense strand, (D) a
base other than G at position 13 of the sense strand, and (E) a base
other than C at position 19 of the sense strand. All variables were
correlated with siRNA silencing of firefly luciferase and human
cyclophilin. siRNAs satisfying the criterion are grouped on the left
(Selected) while those that do not, are grouped on the right
(Eliminated). Y-axis is "% Silencing of Control." Each position on the
X-axis represents a unique siRNA.

[0084]FIGS. 5A and 5B are representations of firefly luciferase and
cyclophilin siRNA panels sorted according to functionality and predicted
values using Formula VIII. The siRNA found within the circle represent
those that have Formula VIII values (SMARTSCORES®, or siRNA rank)
above zero. siRNA outside the indicated area have calculated Formula VIII
values that are below zero. Y-axis is "Expression (% Control)." Each
position on the X-axis represents a unique siRNA.

[0085]FIG. 6A is a representation of the average internal stability
profile (AISP) derived from 270 siRNAs taken from three separate genes
(cyclophilin B, DBI and firefly luciferase). Graphs represent AISP values
of highly functional, functional, and non-functional siRNA. FIG. 6B is a
comparison between the AISP of naturally derived GFP siRNA (filled
squares) and the AISP of siRNA from cyclophilin B, DBI, and luciferase
having >90% silencing properties (no fill) for the antisense strand.
"DG" is the symbol for ΔG, free energy.

[0086]FIG. 7 is a histogram showing the differences in duplex
functionality upon introduction of base pair mismatches. The X-axis shows
the mismatch introduced in the siRNA and the position it is introduced
(e.g., 8C>A reveals that position 8 (which normally has a C) has been
changed to an A). The Y-axis is "% Silencing (Normalized to Control)."
The samples on the X-axis represent siRNAs at 100 nM and are, reading
from left to right: 1A to C, 1A to G, 1A to U; 2A to C, 2A to G, 2A to U;
3A to C, 3A to G, 3A to U; 4G to A, 4G to C; 4G to U; 5U to A, 5U to C,
5U to G; 6U to A, 6U to C, 6U to G; 7G to A, 7G to C, 7G to U; 8C to A,
8C to G, 8C to U; 9G to A, 9G to C, 9G to U; 10C to A, 10C to G, 10C to
U; 11G to A, 11G to C, 11G to U; 12G to A, 12G to C, 12G to U; 13A to C,
13A to G, 13A to U; 14G to A, 14G to C, 14G to U; 15G to A, 15G to C, 15G
to U; 16A to C, 16A to G, 16A to U; 17G to A, 17G to C, 17G to U; 18U to
A, 18U to C, 18U to G; 19U to A, 19U to C, 19U to G; 20 wt; Control.

[0087]FIG. 8 is histogram that shows the effects of 5'sense and antisense
strand modification with 2'-O-methylation on functionality.

[0088]FIG. 9 shows a graph of SMARTSCORES®, or siRNA rank, versus RNAi
silencing values for more than 360 siRNA directed against 30 different
genes. SiRNA to the right of the vertical bar represent those siRNA that
have desirable SMARTSCORES®, or siRNA rank.

[0089]FIGS. 10A-E compare the RNAi of five different genes (SEAP, DBI,
PLK, Firefly Luciferase, and Renilla Luciferase) by varying numbers of
randomly selected siRNA and four rationally designed (SMART-selected)
siRNA chosen using the algorithm described in Formula VIII. In addition,
RNAi induced by a pool of the four SMART-selected siRNA is reported at
two different concentrations (100 and 400 nM). 10F is a comparison
between a pool of randomly selected EGFR siRNA (Pool 1) and a pool of
SMART-selected EGFR siRNA (Pool 2). Pool 1, S1-S4 and Pool 2 S1-S4
represent the individual members that made up each respective pool. Note
that numbers for random siRNAs represent the position of the 5' end of
the sense strand of the duplex. The X-axis indicates the duplex that was
applied. The Y-axis represents the % expression of the control(s).

[0090]FIG. 11 shows the Western blot results from cells treated with siRNA
directed against twelve different genes involved in the
clathrin-dependent endocytosis pathway (CHC, DynII, CALM, CLCa, CLCb,
Eps15, Eps15R, Rab5a, Rab5b, Rab5c, β2 subunit of AP-2 and EEA.1).
siRNA were selected using Formula VIII. "Pool" represents a mixture of
duplexes 1-4. Total concentration of each siRNA in the pool is 25 nM.
Total concentration=4×25=100 nM.

[0099]FIG. 20 shows that the combination of several semifunctional siRNAs
(dark gray) result in a significant improvement of gene expression
inhibition over individual (semi-functional; light gray) siRNA. The
X-axis represents the position of the individual siRNAs that were
measured for effect on expression. The Y-axis represents the percent
expression relative to a control.

[0101]FIG. 22 shows the results of an EGFR and TfnR internalization assay
when single gene knockdowns are performed. The Y-axis represents percent
internalization relative to control.

[0102]FIG. 23 shows the results of an EGFR and TfnR internalization assay
when multiple genes are knocked down (e.g., Rab5a, b, c). The Y-axis
represents the percent internalization relative to control.

[0103]FIG. 24 shows the simultaneous knockdown of four different genes.
siRNAs directed against G6PD, GAPDH, PLK, and UQC were simultaneously
introduced into cells. Twenty-four hours later, cultures were harvested
and assayed for mRNA target levels for each of the four genes. A
comparison is made between cells transfected with individual siRNAs vs. a
pool of siRNAs directed against all four genes.

[0105]Unless stated otherwise, the following terms and phrases have the
meanings provided below:

Complementary

[0106]The term "complementary" refers to the ability of polynucleotides to
form base pairs with one another. Base pairs are typically formed by
hydrogen bonds between nucleotide units in antiparallel polynucleotide
strands. Complementary polynucleotide strands can base pair in the
Watson-Crick manner (e.g., A to T, A to U, C to G), or in any other
manner that allows for the formation of duplexes. As persons skilled in
the art are aware, when using RNA as opposed to DNA, uracil rather than
thymine is the base that is considered to be complementary to adenosine.
However, when a U is denoted in the context of the present invention, the
ability to substitute a T is implied, unless otherwise stated.

[0107]Perfect complementarity or 100% complementarity refers to the
situation in which each nucleotide unit of one polynucleotide strand can
hydrogen bond with a nucleotide unit of a second polynucleotide strand.
Less than perfect complementarity refers to the situation in which some,
but not all, nucleotide units of two strands can hydrogen bond with each
other. For example, for two 20-mers, if only two base pairs on each
strand can hydrogen bond with each other, the polynucleotide strands
exhibit 10% complementarity. In the same example, if 18 base pairs on
each strand can hydrogen bond with each other, the polynucleotide strands
exhibit 90% complementarity.

Deoxynucleotide

[0108]The term "deoxynucleotide" refers to a nucleotide or polynucleotide
lacking a hydroxyl group (OH group) at the 2' and/or 3' position of a
sugar moiety. Instead, it has a hydrogen bonded to the 2' and/or 3'
carbon. Within an RNA molecule that comprises one or more
deoxynucleotides, "deoxynucleotide" refers to the lack of an OH group at
the 2' position of the sugar moiety, having instead a hydrogen bonded
directly to the 2' carbon.

Deoxyribonucleotide

[0109]The terms "deoxyribonucleotide" and "DNA" refer to a nucleotide or
polynucleotide comprising at least one sugar moiety that has an H, rather
than an OH, at its 2' and/or 3'position.

Duplex Region

[0110]The phrase "duplex region" refers to the region in two complementary
or substantially complementary polynucleotides that form base pairs with
one another, either by Watson-Crick base pairing or any other manner that
allows for a stabilized duplex between polynucleotide strands that are
complementary or substantially complementary. For example, a
polynucleotide strand having 21 nucleotide units can base pair with
another polynucleotide of 21 nucleotide units, yet only 19 bases on each
strand are complementary or substantially complementary, such that the
"duplex region" has 19 base pairs. The remaining bases may, for example,
exist as 5' and 3' overhangs. Further, within the duplex region, 100%
complementarity is not required; substantial complementarity is allowable
within a duplex region. Substantial complementarity refers to 79% or
greater complementarity. For example, a mismatch in a duplex region
consisting of 19 base pairs results in 94.7% complementarity, rendering
the duplex region substantially complementary.

Filters

[0111]The term "filter" refers to one or more procedures that are
performed on sequences that are identified by the algorithm. In some
instances, filtering includes in silico procedures where sequences
identified by the algorithm can be screened to identify duplexes carrying
desirable or undesirable motifs. Sequences carrying such motifs can be
selected for, or selected against, to obtain a final set with the
preferred properties. In other instances, filtering includes wet lab
experiments. For instance, sequences identified by one or more versions
of the algorithm can be screened using any one of a number of procedures
to identify duplexes that have hyperfunctional traits (e.g., they exhibit
a high degree of silencing at subnanomolar concentrations and/or exhibit
high degrees of silencing longevity).

Gene Silencing

[0112]The phrase "gene silencing" refers to a process by which the
expression of a specific gene product is lessened or attenuated. Gene
silencing can take place by a variety of pathways. Unless specified
otherwise, as used herein, gene silencing refers to decreases in gene
product expression that results from RNA interference (RNAi), a defined,
though partially characterized pathway whereby small inhibitory RNA
(siRNA) act in concert with host proteins (e.g., the RNA induced
silencing complex, RISC) to degrade messenger RNA (mRNA) in a
sequence-dependent fashion. The level of gene silencing can be measured
by a variety of means, including, but not limited to, measurement of
transcript levels by Northern Blot Analysis, B-DNA techniques,
transcription-sensitive reporter constructs, expression profiling (e.g.,
DNA chips), and related technologies. Alternatively, the level of
silencing can be measured by assessing the level of the protein encoded
by a specific gene. This can be accomplished by performing a number of
studies including Western Analysis, measuring the levels of expression of
a reporter protein that has e.g., fluorescent properties (e.g., GFP) or
enzymatic activity (e.g., alkaline phosphatases), or several other
procedures.

miRNA

[0113]The term "miRNA" refers to microRNA.

Nucleotide

[0114]The term "nucleotide" refers to a ribonucleotide or a
deoxyribonucleotide or modified form thereof, as well as an analog
thereof Nucleotides include species that comprise purines, e.g., adenine,
hypoxanthine, guanine, and their derivatives and analogs, as well as
pyrimidines, e.g., cytosine, uracil, thymine, and their derivatives and
analogs.

[0115]Nucleotide analogs include nucleotides having modifications in the
chemical structure of the base, sugar and/or phosphate, including, but
not limited to, 5-position pyrimidine modifications, 8-position purine
modifications, modifications at cytosine exocyclic amines, and
substitution of 5-bromo-uracil; and 2'-position sugar modifications,
including but not limited to, sugar-modified ribonucleotides in which the
2'-OH is replaced by a group such as an H, OR, R, halo, SH, SR, NH2,
NHR, NR2, or CN, wherein R is an alkyl moiety. Nucleotide analogs
are also meant to include nucleotides with bases such as inosine,
queuosine, xanthine, sugars such as 2'-methyl ribose, non-natural
phosphodiester linkages such as methylphosphonates, phosphorothioates and
peptides.

[0116]Modified bases refer to nucleotide bases such as, for example,
adenine, guanine, cytosine, thymine, uracil, xanthine, inosine, and
queuosine that have been modified by the replacement or addition of one
or more atoms or groups. Some examples of types of modifications that can
comprise nucleotides that are modified with respect to the base moieties
include but are not limited to, alkylated, halogenated, thiolated,
aminated, amidated, or acetylated bases, individually or in combination.
More specific examples include, for example, 5-propynyluridine,
5-propynylcytidine, 6-methyladenine, 6-methylguanine,
N,N,-dimethyladenine, 2-propyladenine, 2-propylguanine, 2-aminoadenine,
1-methylinosine, 3-methyluridine, 5-methylcytidine, 5-methyluridine and
other nucleotides having a modification at the 5 position,
5-(2-amino)propyl uridine, 5-halocytidine, 5-halouridine,
4-acetylcytidine, 1-methyladenosine, 2-methyladenosine, 3-methylcytidine,
6-methyluridine, 2-methylguanosine, 7-methylguanosine,
2,2-dimethylguanosine, 5-methylaminoethyluridine, 5-methyloxyuridine,
deazanucleotides such as 7-deaza-adenosine, 6-azouridine, 6-azocytidine,
6-azothymidine, 5-methyl-2-thiouridine, other thio bases such as
2-thiouridine and 4-thiouridine and 2-thiocytidine, dihydrouridine,
pseudouridine, queuosine, archaeosine, naphthyl and substituted naphthyl
groups, any O-- and N-alkylated purines and pyrimidines such as
N6-methyladenosine, 5-methylcarbonylmethyluridine, uridine 5-oxyacetic
acid, pyridine-4-one, pyridine-2-one, phenyl and modified phenyl groups
such as aminophenol or 2,4,6-trimethoxy benzene, modified cytosines that
act as G-clamp nucleotides, 8-substituted adenines and guanines,
5-substituted uracils and thymines, azapyrimidines, carboxyhydroxyalkyl
nucleotides, carboxyalkylaminoalkyl nucleotides, and
alkylcarbonylalkylated nucleotides. Modified nucleotides also include
those nucleotides that are modified with respect to the sugar moiety, as
well as nucleotides having sugars or analogs thereof that are not
ribosyl. For example, the sugar moieties may be, or be based on,
mannoses, arabinoses, glucopyranoses, galactopyranoses, 4'-thioribose,
and other sugars, heterocycles, or carbocycles.

[0117]The term nucleotide is also meant to include what are known in the
art as universal bases. By way of example, universal bases include but
are not limited to 3-nitropyrrole, 5-nitroindole, or nebularine. The term
"nucleotide" is also meant to include the N3' to P5' phosphoramidate,
resulting from the substitution of a ribosyl 3' oxygen with an amine
group.

[0118]Further, the term nucleotide also includes those species that have a
detectable label, such as for example a radioactive or fluorescent
moiety, or mass label attached to the nucleotide.

Off-Target Silencing and Off-Target Interference

[0119]The phrases "off-target silencing" and "off-target interference" are
defined as degradation of mRNA other than the intended target mRNA due to
overlapping and/or partial homology with secondary mRNA messages.

Polynucleotide

[0120]The term "polynucleotide" refers to polymers of nucleotides, and
includes but is not limited to DNA, RNA, DNA/RNA hybrids including
polynucleotide chains of regularly and/or irregularly alternating
deoxyribosyl moieties and ribosyl moieties (i.e., wherein alternate
nucleotide units have an --OH, then and --H, then an --OH, then an --H,
and so on at the 2' position of a sugar moiety), and modifications of
these kinds of polynucleotides, wherein the attachment of various
entities or moieties to the nucleotide units at any position are
included.

Polyribonucleotide

[0121]The term "polyribonucleotide" refers to a polynucleotide comprising
two or more modified or unmodified ribonucleotides and/or their analogs.
The term "polyribonucleotide" is used interchangeably with the term
"oligoribonucleotide."

Ribonucleotide and Ribonucleic Acid

[0122]The term "ribonucleotide" and the phrase "ribonucleic acid" (RNA),
refer to a modified or unmodified nucleotide or polynucleotide comprising
at least one ribonucleotide unit. A ribonucleotide unit comprises an
hydroxyl group attached to the 2' position of a ribosyl moiety that has a
nitrogenous base attached in N-glycosidic linkage at the 1' position of a
ribosyl moiety, and a moiety that either allows for linkage to another
nucleotide or precludes linkage.

siRNA

[0123]The term "siRNA" refers to small inhibitory RNA duplexes that induce
the RNA interference (RNAi) pathway. These molecules can vary in length
(generally 18-30 base pairs) and contain varying degrees of
complementarity to their target mRNA in the antisense strand. Some, but
not all, siRNA have unpaired overhanging bases on the 5' or 3' end of the
sense strand and/or the antisense strand. The term "siRNA" includes
duplexes of two separate strands, as well as single strands that can form
hairpin structures comprising a duplex region.

[0124]siRNA may be divided into five (5) groups (non-functional,
semi-functional, functional, highly functional, and hyper-functional)
based on the level or degree of silencing that they induce in cultured
cell lines. As used herein, these definitions are based on a set of
conditions where the siRNA is transfected into said cell line at a
concentration of 100 nM and the level of silencing is tested at a time of
roughly 24 hours after transfection, and not exceeding 72 hours after
transfection. In this context, "non-functional siRNA" are defined as
those siRNA that induce less than 50% (<50%) target silencing.
"Semi-functional siRNA" induce 50-79% target silencing. "Functional
siRNA" are molecules that induce 80-95% gene silencing.
"Highly-functional siRNA" are molecules that induce greater than 95% gene
silencing. "Hyperfunctional siRNA" are a special class of molecules. For
purposes of this document, hyperfunctional siRNA are defined as those
molecules that: (1) induce greater than 95% silencing of a specific
target when they are transfected at subnanomolar concentrations (i.e.,
less than one nanomolar); and/or (2) induce functional (or better) levels
of silencing for greater than 96 hours. These relative functionalities
(though not intended to be absolutes) may be used to compare siRNAs to a
particular target for applications such as functional genomics, target
identification and therapeutics.

SMARTSCORE®, or siRNA Rank

[0125]The term "SMARTSCORE®", or "siRNA rank" refers to a number
determined by applying any of the formulas to a given siRNA sequence. The
term "SMART-selected" or "rationally selected" or "rational selection"
refers to siRNA that have been selected on the basis of their
SMARTSCORES®, or siRNA ranking.

Substantially Similar

[0126]The phrase "substantially similar" refers to a similarity of at
least 90% with respect to the identity of the bases of the sequence.

Target

[0127]The term "target" is used in a variety of different forms throughout
this document and is defined by the context in which it is used. "Target
mRNA" refers to a messenger RNA to which a given siRNA can be directed
against. "Target sequence" and "target site" refer to a sequence within
the mRNA to which the sense strand of an siRNA shows varying degrees of
homology and the antisense strand exhibits varying degrees of
complementarity. The phrase "siRNA target" can refer to the gene, mRNA,
or protein against which an siRNA is directed. Similarly, "target
silencing" can refer to the state of a gene, or the corresponding mRNA or
protein.

Transfection

[0128]The term "transfection" refers to a process by which agents are
introduced into a cell. The list of agents that can be transfected is
large and includes, but is not limited to, siRNA, sense and/or anti-sense
sequences, DNA encoding one or more genes and organized into an
expression plasmid, proteins, protein fragments, and more. There are
multiple methods for transfecting agents into a cell including, but not
limited to, electroporation, calcium phosphate-based transfections,
DEAE-dextran-based transfections, lipid-based transfections, molecular
conjugate-based transfections (e.g., polylysine-DNA conjugates),
microinjection and others.

[0129]The present invention is directed to improving the efficiency of
gene silencing by siRNA. Through the inclusion of multiple siRNA
sequences that are targeted to a particular gene and/or selecting an
siRNA sequence based on certain defined criteria, improved efficiency may
be achieved.

[0130]The present invention will now be described in connection with
preferred embodiments. These embodiments are presented in order to aid in
an understanding of the present invention and are not intended, and
should not be construed, to limit the invention in any way. All
alternatives, modifications and equivalents that may become apparent to
those of ordinary skill upon reading this disclosure are included within
the spirit and scope of the present invention.

[0131]Furthermore, this disclosure is not a primer on RNA interference.
Basic concepts known to persons skilled in the art have not been set
forth in detail.

[0133]According to a first embodiment, the present invention provides a
kit for gene silencing, wherein said kit is comprised of a pool of at
least two siRNA duplexes, each of which is comprised of a sequence that
is complementary to a portion of the sequence of one or more target
messenger RNA, and each of which is selected using non-target specific
criteria. Each of the at least two siRNA duplexes of the kit
complementary to a portion of the sequence of one or more target mRNAs is
preferably selected using Formula X.

[0134]According to a second embodiment, the present invention provides a
method for selecting an siRNA, said method comprising applying selection
criteria to a set of potential siRNA that comprise 18-30 base pairs,
wherein said selection criteria are non-target specific criteria, and
said set comprises at least two siRNAs and each of said at least two
siRNAs contains a sequence that is at least substantially complementary
to a target gene; and determining the relative functionality of the at
least two siRNAs.

[0135]In one embodiment, the present invention also provides a method
wherein said selection criteria are embodied in a formula comprising:

(-8)*A1+(-1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(-4)*A9+(-5)-
*A10+(-2)*A11+(-5)*A12+(17)*A13+(-3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+-
(30)*A19+(-13)*U1+(-10)*U2+(2)*U3+(-2)*U4+(-5)*U5+(5)*U6+(-2)*U7+(-10)*U8+-
(-5)*U9+(15)*U10+(-1)*U11+(0)*U12+(10)*U13+(-9)*U14+(-13)*U15+(-10)*U16+(3-
)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(-21)*C3+(5)*C4+(-9)*C5+(-20)*C6+(-18)-
*C7+(-5)*C8+(5)*C9+(1)*C10+(2)*C11+(-5)*C12+(-3)*C13+(-6)*C14+(-2)*C15+(-5-
)*C16+(-3)*C17+(-12)*C18+(-18)*C19+(14)*G1+(8)*G2+(7)*G3+(-10)*G4+(-4)*G5+-
(2)*G6+(1)*G7+(9)*G8+(5)*G9+(-11)*G10+(1)*G11+(9)*G12+(-24)*G13+(18)*G14+(-
11)*G15+(13)*G16+(-7)*G17+(-9)*G18+(-22)*G19+6*(number of A+U in position
15-19)-3*(number of G+C in whole siRNA), Formula X [0136]wherein
position numbering begins at the 5'-most position of a sense strand, and
[0137]A1=1 if A is the base at position 1 of the sense strand,
otherwise its value is 0; [0138]A2=1 if A is the base at position 2
of the sense strand, otherwise its value is 0; [0139]A3=1 if A is
the base at position 3 of the sense strand, otherwise its value is 0;
[0140]A4=1 if A is the base at position 4 of the sense strand,
otherwise its value is 0; [0141]A5=1 if A is the base at position 5
of the sense strand, otherwise its value is 0; [0142]A6=1 if A is
the base at position 6 of the sense strand, otherwise its value is 0;
[0143]A7=1 if A is the base at position 7 of the sense strand,
otherwise its value is 0; [0144]A10=1 if A is the base at position
10 of the sense strand, otherwise its value is 0; [0145]A11=1 if A
is the base at position 11 of the sense strand, otherwise its value is 0;
[0146]A13=1 if A is the base at position 13 of the sense strand,
otherwise its value is 0; [0147]A19=1 if A is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0148]C3=1
if C is the base at position 3 of the sense strand, otherwise its value
is 0; [0149]C4=1 if C is the base at position 4 of the sense strand,
otherwise its value is 0; [0150]C5=1 if C is the base at position 5
of the sense strand, otherwise its value is 0; [0151]C6=1 if C is
the base at position 6 of the sense strand, otherwise its value is 0;
[0152]C7=1 if C is the base at position 7 of the sense strand,
otherwise its value is 0; [0153]C9=1 if C is the base at position 9
of the sense strand, otherwise its value is 0; [0154]C17=1 if C is
the base at position 17 of the sense strand, otherwise its value is 0;
[0155]C18=1 if C is the base at position 18 of the sense strand,
otherwise its value is 0; [0156]C19=1 if C is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0157]G1=1
if G is the base at position 1 on the sense strand, otherwise its value
is 0; [0158]G2=1 if G is the base at position 2 of the sense strand,
otherwise its value is 0; [0159]G8=1 if G is the base at position 8
on the sense strand, otherwise its value is 0; [0160]G10=1 if G is
the base at position 10 on the sense strand, otherwise its value is 0;
[0161]G13=1 if G is the base at position 13 on the sense strand,
otherwise its value is 0; [0162]G19=1 if G is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0163]U1=1
if U is the base at position 1 on the sense strand, otherwise its value
is 0; [0164]U2=1 if U is the base at position 2 on the sense strand,
otherwise its value is 0; [0165]U3=1 if U is the base at position 3
on the sense strand, otherwise its value is 0; [0166]U4=1 if U is
the base at position 4 on the sense strand, otherwise its value is 0;
[0167]U7=1 if U is the base at position 7 on the sense strand,
otherwise its value is 0; [0168]U9=1 if U is the base at position 9
on the sense strand, otherwise its value is 0; [0169]U10=1 if U is
the base at position 10 on the sense strand, otherwise its value is 0;
[0170]U15=1 if U is the base at position 15 on the sense strand,
otherwise its value is 0; [0171]U16=1 if U is the base at position
16 on the sense strand, otherwise its value is 0; [0172]U17=1 if U
is the base at position 17 on the sense strand, otherwise its value is 0;
[0173]U18=1 if U is the base at position 18 on the sense strand,
otherwise its value is 0. [0174]GC15-19=the number of G and C bases
within positions 15-19 of the sense strand, or within positions 15-18 if
the sense strand is only 18 base pairs in length; [0175]GCtotal=the
number of G and C bases in the sense strand; [0176]Tm=100 if the siRNA
oligo has the internal repeat longer then 4 base pairs, otherwise its
value is 0; and [0177]X=the number of times that the same nucleotide
repeats four or more times in a row.

[0178]Any of the methods of selecting siRNA in accordance with the
invention can further comprise comparing the internal stability profiles
of the siRNAs to be selected, and selecting those siRNAs with the most
favorable internal stability profiles. Any of the methods of selecting
siRNA can further comprise selecting either for or against sequences that
contain motifs that induce cellular stress. Such motifs include, for
example, toxicity motifs. Any of the methods of selecting siRNA can
further comprise either selecting for or selecting against sequences that
comprise stability motifs.

[0179]In another embodiment, the present invention provides a method of
gene silencing, comprising introducing into a cell at least one siRNA
selected according to any of the methods of the present invention. The
siRNA can be introduced by allowing passive uptake of siRNA, or through
the use of a vector.

[0180]According to a third embodiment, the invention provides a method for
developing an algorithm for selecting siRNA, said method comprising: (a)
selecting a set of siRNA; (b) measuring gene silencing ability of each
siRNA from said set; (c) determining relative functionality of each
siRNA; (d) determining improved functionality by the presence or absence
of at least one variable selected from the group consisting of the
presence or absence of a particular nucleotide at a particular position,
the total number of As and Us in positions 15-19, the number of times
that the same nucleotide repeats within a given sequence, and the total
number of Gs and Cs; and (e) developing an algorithm using the
information of step (d).

[0181]In another embodiment, the invention provides a method for selecting
an siRNA with improved functionality, comprising using the
above-mentioned algorithm to identify an siRNA of improved functionality.

[0182]According to a fourth embodiment, the present invention provides a
kit, wherein said kit is comprised of at least two siRNAs, wherein said
at least two siRNAs comprise a first optimized siRNA and a second
optimized siRNA, wherein said first optimized siRNA and said second
optimized siRNA are optimized according a formula comprising Formula X.

[0183]According to a fifth embodiment, the present invention provides a
method for identifying a hyperfunctional siRNA, comprising applying
selection criteria to a set of potential siRNA that comprise 18-30 base
pairs, wherein said selection criteria are non-target specific criteria,
and said set comprises at least two siRNAs and each of said at least two
siRNAs contains a sequence that is at least substantially complementary
to a target gene; determining the relative functionality of the at least
two siRNAs and assigning each of the at least two siRNAs a functionality
score; and selecting siRNAs from the at least two siRNAs that have a
functionality score that reflects greater than 80 percent silencing at a
concentration in the picomolar range, wherein said greater than 80
percent silencing endures for greater than 120 hours.

[0184]In other embodiments, the invention provides kits and/or methods
wherein the siRNA are comprised of two separate polynucleotide strands;
wherein the siRNA are comprised of a single contiguous molecule such as,
for example, a unimolecular siRNA (comprising, for example, either a
nucleotide or non-nucleotide loop); wherein the siRNA are expressed from
one or more vectors; and wherein two or more genes are silenced by a
single administration of siRNA.

[0185]According to a sixth embodiment, the present invention provides a
hyperfunctional siRNA that is capable of silencing Bcl2.

[0186]According to a seventh embodiment, the present invention provides a
method for developing an siRNA algorithm for selecting functional and
hyperfunctional siRNAs for a given sequence. The method comprises:

[0187](a) selecting a set of siRNAs;

[0188](b) measuring the gene silencing ability of each siRNA from said
set;

[0189](c) determining the relative functionality of each siRNA;

[0190](d) determining the amount of improved functionality by the presence
or absence of at least one variable selected from the group consisting of
the total GC content, melting temperature of the siRNA, GC content at
positions 15-19, the presence or absence of a particular nucleotide at a
particular position, relative thermodynamic stability at particular
positions in a duplex, and the number of times that the same nucleotide
repeats within a given sequence; and

[0191](e) developing an algorithm using the information of step (d).

[0192]According to this embodiment, preferably the set of siRNAs comprises
at least 90 siRNAs from at least one gene, more preferably at least 180
siRNAs from at least two different genes, and most preferably at least
270 and 360 siRNAs from at least three and four different genes,
respectively. Additionally, in step (d) the determination is made with
preferably at least two, more preferably at least three, even more
preferably at least four, and most preferably all of the variables. The
resulting algorithm is not target sequence specific.

[0193]In another embodiment, the present invention provides rationally
designed siRNAs identified using the formulas above.

[0194]In yet another embodiment, the present invention is directed to
hyperfunctional siRNA.

[0195]The ability to use the above algorithms, which are not sequence or
species specific, allows for the cost-effective selection of optimized
siRNAs for specific target sequences. Accordingly, there will be both
greater efficiency and reliability in the use of siRNA technologies.

[0196]The methods disclosed herein can be used in conjunction with
comparing internal stability profiles of selected siRNAs, and designing
an siRNA with a desirable internal stability profile; and/or in
conjunction with a selection either for or against sequences that contain
motifs that induce cellular stress, for example, cellular toxicity.

[0197]Any of the methods disclosed herein can be used to silence one or
more genes by introducing an siRNA selected, or designed, in accordance
with any of the methods disclosed herein. The siRNA(s) can be introduced
into the cell by any method known in the art, including passive uptake or
through the use of one or more vectors.

[0198]Any of the methods and kits disclosed herein can employ either
unimolecular siRNAs, siRNAs comprised of two separate polynucleotide
strands, or combinations thereof. Any of the methods disclosed herein can
be used in gene silencing, where two or more genes are silenced by a
single administration of siRNA(s). The siRNA(s) can be directed against
two or more target genes, and administered in a single dose or single
transfection, as the case may be.

Optimizing siRNA

[0199]According to one embodiment, the present invention provides a method
for improving the effectiveness of gene silencing for use to silence a
particular gene through the selection of an optimal siRNA. An siRNA
selected according to this method may be used individually, or in
conjunction with the first embodiment, i.e., with one or more other
siRNAs, each of which may or may not be selected by this criteria in
order to maximize their efficiency.

[0200]The degree to which it is possible to select an siRNA for a given
mRNA that maximizes these criteria will depend on the sequence of the
mRNA itself. However, the selection criteria will be independent of the
target sequence. According to this method, an siRNA is selected for a
given gene by using a rational design. That said, rational design can be
described in a variety of ways. Rational design is, in simplest terms,
the application of a proven set of criteria that enhance the probability
of identifying a functional or hyperfunctional siRNA. In one method,
rationally designed siRNA can be identified by maximizing one or more of
the following criteria: [0201](1) A low GC content, preferably between
about 30-52%. [0202](2) At least 2, preferably at least 3 A or U bases at
positions 15-19 of the siRNA on the sense strand. [0203](3) An A base at
position 19 of the sense strand. [0204](4) An A base at position 3 of the
sense strand. [0205](5) A U base at position 10 of the sense strand.
[0206](6) An A base at position 14 of the sense strand. [0207](7) A base
other than C at position 19 of the sense strand. [0208](8) A base other
than G at position 13 of the sense strand. [0209](9) A Tm, which refers
to the character of the internal repeat that results in inter- or
intramolecular structures for one strand of the duplex, that is
preferably not stable at greater than 50° C., more preferably not
stable at greater than 37° C., even more preferably not stable at
greater than 30° C. and most preferably not stable at greater than
20° C. [0210](10) A base other than U at position 5 of the sense
strand. [0211](11) A base other than A at position 11 of the sense
strand. [0212](12) A base other than an A at position 1 of the sense
strand. [0213](13) A base other than an A at position 2 of the sense
strand. [0214](14) An A base at position 4 of the sense strand.
[0215](15) An A base at position 5 of the sense strand. [0216](16) An A
base at position 6 of the sense strand. [0217](17) An A base at position
7 of the sense strand. [0218](18) An A base at position 8 of the sense
strand. [0219](19) A base other than an A at position 9 of the sense
strand. [0220](20) A base other than an A at position 10 of the sense
strand. [0221](21) A base other than an A at position 11 of the sense
strand. [0222](22) A base other than an A at position 12 of the sense
strand. [0223](23) An A base at position 13 of the sense strand.
[0224](24) A base other than an A at position 14 of the sense strand.
[0225](25) An A base at position 15 of the sense strand [0226](26) An A
base at position 16 of the sense strand. [0227](27) An A base at position
17 of the sense strand. [0228](28) An A base at position 18 of the sense
strand. [0229](29) A base other than a U at position 1 of the sense
strand. [0230](30) A base other than a U at position 2 of the sense
strand. [0231](31) A U base at position 3 of the sense strand. [0232](32)
A base other than a U at position 4 of the sense strand. [0233](33) A
base other than a U at position 5 of the sense strand. [0234](34) A U
base at position 6 of the sense strand. [0235](35) A base other than a U
at position 7 of the sense strand. [0236](36) A base other than a U at
position 8 of the sense strand. [0237](37) A base other than a U at
position 9 of the sense strand. [0238](38) A base other than a U at
position 11 of the sense strand. [0239](39) A U base at position 13 of
the sense strand. [0240](40) A base other than a U at position 14 of the
sense strand. [0241](41) A base other than a U at position 15 of the
sense strand. [0242](42) A base other than a U at position 16 of the
sense strand. [0243](43) A U base at position 17 of the sense strand.
[0244](44) A U base at position 18 of the sense strand. [0245](45) A U
base at position 19 of the sense strand. [0246](46) A C base at position
1 of the sense strand. [0247](47) A C base at position 2 of the sense
strand. [0248](48) A base other than a C at position 3 of the sense
strand. [0249](49) A C base at position 4 of the sense strand. [0250](50)
A base other than a C at position 5 of the sense strand. [0251](51) A
base other than a C at position 6 of the sense strand. [0252](52) A base
other than a C at position 7 of the sense strand. [0253](53) A base other
than a C at position 8 of the sense strand. [0254](54) A C base at
position 9 of the sense strand. [0255](55) A C base at position 10 of the
sense strand. [0256](56) A C base at position 11 of the sense strand.
[0257](57) A base other than a C at position 12 of the sense strand.
[0258](58) A base other than a C at position 13 of the sense strand.
[0259](59) A base other than a C at position 14 of the sense strand.
[0260](60) A base other than a C at position 15 of the sense strand.
[0261](61) A base other than a C at position 16 of the sense strand.
[0262](62) A base other than a C at position 17 of the sense strand.
[0263](63) A base other than a C at position 18 of the sense strand.
[0264](64) A G base at position 1 of the sense strand. [0265](65) A G
base at position 2 of the sense strand. [0266](66) A G base at position 3
of the sense strand. [0267](67) A base other than a G at position 4 of
the sense strand. [0268](68) A base other than a G at position 5 of the
sense strand. [0269](69) A G base at position 6 of the sense strand.
[0270](70) A G base at position 7 of the sense strand. [0271](71) A G
base at position 8 of the sense strand. [0272](72) A G base at position 9
of the sense strand. [0273](73) A base other than a G at position 10 of
the sense strand. [0274](74) A G base at position 11 of the sense strand.
[0275](75) A G base at position 12 of the sense strand. [0276](76) A G
base at position 14 of the sense strand. [0277](77) A G base at position
15 of the sense strand. [0278](78) A G base at position 16 of the sense
strand. [0279](79) A base other than a G at position 17 of the sense
strand. [0280](80) A base other than a G at position 18 of the sense
strand. [0281](81) A base other than a G at position 19 of the sense
strand.

[0282]The importance of various criteria can vary greatly. For instance, a
C base at position 10 of the sense strand makes a minor contribution to
duplex functionality. In contrast, the absence of a C at position 3 of
the sense strand is very important. Accordingly, preferably an siRNA will
satisfy as many of the aforementioned criteria as possible.

[0283]With respect to the criteria, GC content, as well as a high number
of AU in positions 15-19 of the sense strand, may be important for
easement of the unwinding of double stranded siRNA duplex. Duplex
unwinding has been shown to be crucial for siRNA functionality in vivo.

[0284]With respect to criterion 9, the internal structure is measured in
terms of the melting temperature of the single strand of siRNA, which is
the temperature at which 50% of the molecules will become denatured. With
respect to criteria 2-8 and 10-11, the positions refer to sequence
positions on the sense strand, which is the strand that is identical to
the mRNA.

[0285]In one preferred embodiment, at least criteria 1 and 8 are
satisfied. In another preferred embodiment, at least criteria 7 and 8 are
satisfied. In still another preferred embodiment, at least criteria 1, 8
and 9 are satisfied.

[0286]It should be noted that all of the aforementioned criteria regarding
sequence position specifics are with respect to the 5' end of the sense
strand. Reference is made to the sense strand, because most databases
contain information that describes the information of the mRNA. Because
according to the present invention a chain can be from 18 to 30 bases in
length, and the aforementioned criteria assumes a chain 19 base pairs in
length, it is important to keep the aforementioned criteria applicable to
the correct bases.

[0287]When there are only 18 bases, the base pair that is not present is
the base pair that is located at the 3' of the sense strand. When there
are twenty to thirty bases present, then additional bases are added at
the 5' end of the sense chain and occupy positions -1 to -11.
Accordingly, with respect to SEQ. ID NO. 0001 NNANANNNNUCNAANNNNA and
SEQ. ID NO. 0028 GUCNNANANNNNUCNAANNNNA, both would have A at position 3,
A at position 5, U at position 10, C at position 11, A and position 13, A
and position 14 and A at position 19. However, SEQ. ID NO. 0028 would
also have C at position -1, U at position -2 and G at position -3.

[0288]For a 19 base pair siRNA, an optimal sequence of one of the strands
may be represented below, where N is any base, A, C, G, or U:

[0290]In Formulas I-VII: [0291]wherein A19=1 if A is the base at
position 19 on the sense strand, otherwise its value is 0,
[0292]AU15-19=0-5 depending on the number of A or U bases on the
sense strand at positions 15 -19; [0293]G13=1 if G is the base at
position 13 on the sense strand, otherwise its value is 0;
[0294]C19=1 if C is the base at position 19 of the sense strand,
otherwise its value is 0; [0295]GC=the number of G and C bases in the
entire sense strand; [0296]Tm20° C.=1 if the Tm is greater
than 20° C.; [0297]A3=1 if A is the base at position 3 on the
sense strand, otherwise its value is 0; [0298]U10=1 if U is the base
at position 10 on the sense strand, otherwise its value is 0;
[0299]A14=1 if A is the base at position 14 on the sense strand,
otherwise its value is 0; [0300]U5=1 if U is the base at position 5
on the sense strand, otherwise its value is 0; and [0301]A11=1 if A
is the base at position 11 of the sense strand, otherwise its value is 0.

[0302]Formulas I-VII provide relative information regarding functionality.
When the values for two sequences are compared for a given formula, the
relative functionality is ascertained; a higher positive number indicates
a greater functionality. For example, in many applications a value of 5
or greater is beneficial.

[0303]Additionally, in many applications, more than one of these formulas
would provide useful information as to the relative functionality of
potential siRNA sequences. However, it is beneficial to have more than
one type of formula, because not every formula will be able to help to
differentiate among potential siRNA sequences. For example, in
particularly high GC mRNAs, formulas that take that parameter into
account would not be useful and application of formulas that lack GC
elements (e.g., formulas V and VI) might provide greater insights into
duplex functionality. Similarly, formula II might by used in situations
where hairpin structures are not observed in duplexes, and formula IV
might be applicable for sequences that have higher AU content. Thus, one
may consider a particular sequence in light of more than one or even all
of these algorithms to obtain the best differentiation among sequences.
In some instances, application of a given algorithm may identify an
unusually large number of potential siRNA sequences, and in those cases,
it may be appropriate to re-analyze that sequence with a second algorithm
that is, for instance, more stringent. Alternatively, it is conceivable
that analysis of a sequence with a given formula yields no acceptable
siRNA sequences (i.e. low SMARTSCORES®, or siRNA ranking). In this
instance, it may be appropriate to re-analyze that sequences with a
second algorithm that is, for instance, less stringent. In still other
instances, analysis of a single sequence with two separate formulas may
give rise to conflicting results (i.e. one formula generates a set of
siRNA with high SMARTSCORES®, or siRNA ranking, while the other
formula identifies a set of siRNA with low SMARTSCORES®, or siRNA
ranking). In these instances, it may be necessary to determine which
weighted factor(s) (e.g. GC content) are contributing to the discrepancy
and assessing the sequence to decide whether these factors should or
should not be included. Alternatively, the sequence could be analyzed by
a third, fourth, or fifth algorithm to identify a set of rationally
designed siRNA.

[0304]The above-referenced criteria are particularly advantageous when
used in combination with pooling techniques as depicted in Table I:

[0305]The term "current" used in Table I refers to Tuschl's conventional
siRNA parameters (Elbashir, S. M. et al. (2002) "Analysis of gene
function in somatic mammalian cells using small interfering RNAs" Methods
26: 199-213). "New" refers to the design parameters described in Formulas
I-VII. "GC" refers to criteria that select siRNA solely on the basis of
GC content.

[0306]As Table I indicates, when more functional siRNA duplexes are
chosen, siRNAs that produce <70% silencing drops from 23% to 8% and
the number of siRNA duplexes that produce >80% silencing rises from
50% to 88.5%. Further, of the siRNA duplexes with >80% silencing, a
larger portion of these siRNAs actually silence >95% of the target
expression (the new criteria increases the portion from 33% to 50%).
Using this new criteria in pooled siRNAs, shows that, with pooling, the
amount of silencing >95% increases from 79.5% to 93.8% and essentially
eliminates any siRNA pool from silencing less than 70%.

[0307]Table II similarly shows the particularly beneficial results of
pooling in combination with the aforementioned criteria. However, Table
II, which takes into account each of the aforementioned variables,
demonstrates even a greater degree of improvement in functionality.

[0309]The above-described algorithms may be used with or without a
computer program that allows for the inputting of the sequence of the
mRNA and automatically outputs the optimal siRNA. The computer program
may, for example, be accessible from a local terminal or personal
computer, over an internal network or over the Internet.

[0310]In addition to the formulas above, more detailed algorithms may be
used for selecting siRNA. Preferably, at least one RNA duplex of 18-30
base pairs is selected such that it is optimized according a formula
selected from:

(-8)*A1+(-1)*A2+(12)*A3+(7)*A4+(18)*A5+(12)*A6+(19)*A7+(6)*A8+(-4)*A9+(-5)-
*A10+(-2)*A11+(-5)*A12+(17)*A13+(-3)*A14+(4)*A15+(2)*A16+(8)*A17+(11)*A18+-
(30)*A19+(-13)*U1+(-10)*U2+(2)*U3+(-2)*U4+(-5)*U5+(5)*U6+(-2)*U7+(-10)*U8+-
(-5)*U9+(15)*U10+(-1)*U11+(0)*U12+(10)*U13+(-9)*U14+(-13)*U15+(-10)*U16+(3-
)*U17+(9)*U18+(9)*U19+(7)*C1+(3)*C2+(-21)*C3+(5)*C4+(-9)*C5+(-20)*C6+(-18)-
*C7+(-5)*C8+(5)*C9+(1)*C10+(2)*C11+(-5)*C12+(-3)*C13+(-6)*C14+(-2)*C15+(-5-
)*C16+(-3)*C17+(-12)*C18+(-18)*C19+(14)*G1+(8)*G2+(7)*G3+(-10)*G4+(-4)*G5+-
(2)*G6+(1)*G7+(9)*G8+(5)*G9+(-11)*G10+(1)*G11+(9)*G12+(-24)*G13+(18)*G14+(-
11)*G15+(13)*G16+(-7)*G17+(-9)*G18+(-22)*G19+6*(number of A+U in position
15-19)-3*(number of G+C in whole siRNA). Formula X: [0311]wherein
[0312]A1=1 if A is the base at position 1 of the sense strand,
otherwise its value is 0; [0313]A2=1 if A is the base at position 2
of the sense strand, otherwise its value is 0; [0314]A3=1 if A is
the base at position 3 of the sense strand, otherwise its value is 0;
[0315]A4=1 if A is the base at position 4 of the sense strand,
otherwise its value is 0; [0316]A5=1 if A is the base at position 5
of the sense strand, otherwise its value is 0; [0317]A6=1 if A is
the base at position 6 of the sense strand, otherwise its value is 0;
[0318]A7=1 if A is the base at position 7 of the sense strand,
otherwise its value is 0; [0319]A10=1 if A is the base at position
10 of the sense strand, otherwise its value is 0; [0320]A11=1 if A
is the base at position 11 of the sense strand, otherwise its value is 0;
[0321]A13=1 if A is the base at position 13 of the sense strand,
otherwise its value is 0; [0322]A19=1 if A is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0323]C3=1
if C is the base at position 3 of the sense strand, otherwise its value
is 0; [0324]C4=1 if C is the base at position 4 of the sense strand,
otherwise its value is 0; [0325]C5=1 if C is the base at position 5
of the sense strand, otherwise its value is 0; [0326]C6=1 if C is
the base at position 6 of the sense strand, otherwise its value is 0;
[0327]C7=1 if C is the base at position 7 of the sense strand,
otherwise its value is 0; [0328]C9=1 if C is the base at position 9
of the sense strand, otherwise its value is 0; [0329]C17=1 if C is
the base at position 17 of the sense strand, otherwise its value is 0;
[0330]C18=1 if C is the base at position 18 of the sense strand,
otherwise its value is 0; [0331]C19=1 if C is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0332]G1=1
if G is the base at position 1 on the sense strand, otherwise its value
is 0; [0333]G2=1 if G is the base at position 2 of the sense strand,
otherwise its value is 0; [0334]G8=1 if G is the base at position 8
on the sense strand, otherwise its value is 0; [0335]G10=1 if G is
the base at position 10 on the sense strand, otherwise its value is 0;
[0336]G13=1 if G is the base at position 13 on the sense strand,
otherwise its value is 0; [0337]G19=1 if G is the base at position
19 of the sense strand, otherwise if another base is present or the sense
strand is only 18 base pairs in length, its value is 0; [0338]U1=1
if U is the base at position 1 on the sense strand, otherwise its value
is 0; [0339]U2=1 if U is the base at position 2 on the sense strand,
otherwise its value is 0; [0340]U3=1 if U is the base at position 3
on the sense strand, otherwise its value is 0; [0341]U4=1 if U is
the base at position 4 on the sense strand, otherwise its value is 0;
[0342]U7=1 if U is the base at position 7 on the sense strand,
otherwise its value is 0; [0343]U9=1 if U is the base at position 9
on the sense strand, otherwise its value is 0; [0344]U10=1 if U is
the base at position 10 on the sense strand, otherwise its value is 0;
[0345]U15=1 if U is the base at position 15 on the sense strand,
otherwise its value is 0; [0346]U16=1 if U is the base at position
16 on the sense strand, otherwise its value is 0; [0347]U17=1 if U
is the base at position 17 on the sense strand, otherwise its value is 0;
[0348]U18=1 if U is the base at position 18 on the sense strand,
otherwise its value is 0; [0349]GC15-19=the number of G and C bases
within positions 15-19 of the sense strand, or within positions 15-18 if
the sense strand is only 18 base pairs in length; [0350]GCtotal=the
number of G and C bases in the sense strand; [0351]Tm=100 if the siRNA
oligo has the internal repeat longer then 4 base pairs, otherwise its
value is 0; and [0352]X=the number of times that the same nucleotide
repeats four or more times in a row.

[0353]The above formulas VIII, IX, and X, as well as formulas I-VII,
provide methods for selecting siRNA in order to increase the efficiency
of gene silencing. A subset of variables of any of the formulas may be
used, though when fewer variables are used, the optimization hierarchy
becomes less reliable.

[0354]With respect to the variables of the above-referenced formulas, a
single letter of A or C or G or U followed by a subscript refers to a
binary condition. The binary condition is that either the particular base
is present at that particular position (wherein the value is "1") or the
base is not present (wherein the value is "0"). Because position 19 is
optional, i.e., there might be only 18 base pairs, when there are only 18
base pairs, any base with a subscript of 19 in the formulas above would
have a zero value for that parameter. Before or after each variable is a
number followed by *, which indicates that the value of the variable is
to be multiplied or weighed by that number.

[0355]The numbers preceding the variables A, or G, or C, or U in Formulas
VIII, IX, and X (or after the variables in Formula I-VII) were determined
by comparing the difference in the frequency of individual bases at
different positions in functional siRNA and total siRNA. Specifically,
the frequency in which a given base was observed at a particular position
in functional groups was compared with the frequency that that same base
was observed in the total, randomly selected siRNA set. If the absolute
value of the difference between the functional and total values was found
to be greater than 6%, that parameter was included in the equation. Thus,
for instance, if the frequency of finding a "G" at position 13 (G13)
is found to be 6% in a given functional group, and the frequency of
G13 in the total population of siRNAs is 20%, the difference between
the two values is 6%-20%=-14%. As the absolute value is greater than six
(6), this factor (-14) is included in the equation. Thus, in Formula
VIII, in cases where the siRNA under study has a G in position 13, the
accrued value is (-14)*(1)=-14. In contrast, when a base other than G is
found at position 13, the accrued value is (-14)*(0)=0.

[0356]When developing a means to optimize siRNAs, the inventors observed
that a bias toward low internal thermodynamic stability of the duplex at
the 5'-antisense (AS) end is characteristic of naturally occurring miRNA
precursors. The inventors extended this observation to siRNAs for which
functionality had been assessed in tissue culture.

[0357]With respect to the parameter GC15-19, a value of 0-5 will be
ascribed depending on the number of G or C bases at positions 15 to 19.
If there are only 18 base pairs, the value is between 0 and 4.

[0358]With respect to the criterion GCtotal content, a number from
0-30 will be ascribed, which correlates to the total number of G and C
nucleotides on the sense strand, excluding overhangs. Without wishing to
be bound by any one theory, it is postulated that the significance of the
GC content (as well as AU content at positions 15-19, which is a
parameter for formulas III-VII) relates to the easement of the unwinding
of a double-stranded siRNA duplex. Duplex unwinding is believed to be
crucial for siRNA functionality in vivo and overall low internal
stability, especially low internal stability of the first unwound base
pair is believed to be important to maintain sufficient processivity of
RISC complex-induced duplex unwinding. If the duplex has 19 base pairs,
those at positions 15-19 on the sense strand will unwind first if the
molecule exhibits a sufficiently low internal stability at that position.
As persons skilled in the art are aware, RISC is a complex of
approximately twelve proteins; Dicer is one, but not the only, helicase
within this complex. Accordingly, although the GC parameters are believed
to relate to activity with Dicer, they are also important for activity
with other RISC proteins.

[0359]The value of the parameter Tm is 0 when there are no internal
repeats longer than (or equal to) four base pairs present in the siRNA
duplex; otherwise the value is 1. Thus for example, if the sequence
ACGUACGU, or any other four nucleotide (or more) palindrome exists within
the structure, the value will be one (1). Alternatively if the structure
ACGGACG, or any other 3 nucleotide (or less) palindrome exists, the value
will be zero (0).

[0360]The variable "X" refers to the number of times that the same
nucleotide occurs contiguously in a stretch of four or more units. If
there are, for example, four contiguous As in one part of the sequence
and elsewhere in the sequence four contiguous Cs, X=2. Further, if there
are two separate contiguous stretches of four of the same nucleotides or
eight or more of the same nucleotides in a row, then X=2. However, X does
not increase for five, six or seven contiguous nucleotides.

[0361]Again, when applying Formula VIII, Formula IX, or Formula X, to a
given mRNA, (the "target RNA" or "target molecule"), one may use a
computer program to evaluate the criteria for every sequence of 18-30
base pairs or only sequences of a fixed length, e.g., 19 base pairs.
Preferably the computer program is designed such that it provides a
report ranking of all of the potential siRNAs 18-30 base pairs, ranked
according to which sequences generate the highest value. A higher value
refers to a more efficient siRNA for a particular target gene. The
computer program that may be used may be developed in any computer
language that is known to be useful for scoring nucleotide sequences, or
it may be developed with the assistance of commercially available product
such as Microsoft's PRODUCT.NET. Additionally, rather than run every
sequence through one and/or another formula, one may compare a subset of
the sequences, which may be desirable if for example only a subset are
available. For instance, it may be desirable to first perform a BLAST
(Basic Local Alignment Search Tool) search and to identify sequences that
have no homology to other targets. Alternatively, it may be desirable to
scan the sequence and to identify regions of moderate GC context, then
perform relevant calculations using one of the above-described formulas
on these regions. These calculations can be done manually or with the aid
of a computer.

[0362]As with Formulas I-VII, either Formula VIII, Formula IX, or Formula
X may be used for a given mRNA target sequence. However, it is possible
that according to one or the other formula more than one siRNA will have
the same value. Accordingly, it is beneficial to have a second formula by
which to differentiate sequences. Formulas IX and X were derived in a
similar fashion as Formula VIII, yet used a larger data set and thus
yields sequences with higher statistical correlations to highly
functional duplexes. The sequence that has the highest value ascribed to
it may be referred to as a "first optimized duplex." The sequence that
has the second highest value ascribed to it may be referred to as a
"second optimized duplex." Similarly, the sequences that have the third
and fourth highest values ascribed to them may be referred to as a third
optimized duplex and a fourth optimized duplex, respectively. When more
than one sequence has the same value, each of them may, for example, be
referred to as first optimized duplex sequences or co-first optimized
duplexes. Formula X is similar to Formula IX, yet uses a greater numbers
of variables and for that reason, identifies sequences on the basis of
slightly different criteria.

[0363]It should also be noted that the output of a particular algorithm
will depend on several of variables including: (1) the size of the data
base(s) being analyzed by the algorithm, and (2) the number and
stringency of the parameters being applied to screen each sequence. Thus,
for example, in U.S. patent application Ser. No. 10/714,333, entitled
"Functional and Hyperfunctional siRNA," filed Nov. 14, 2003, Formula VIII
was applied to the known human genome (NCBI REFSEQ database) through
ENTREZ (EFETCH). As a result of these procedures, roughly 1.6 million
siRNA sequences were identified. Application of Formula VIII to the same
database in March of 2004 yielded roughly 2.2 million sequences, a
difference of approximately 600,000 sequences resulting from the growth
of the database over the course of the months that span this period of
time. Application of other formulas (e.g., Formula X) that change the
emphasis of, include, or eliminate different variables can yield unequal
numbers of siRNAs. Alternatively, in cases where application of one
formula to one or more genes fails to yield sufficient numbers of siRNAs
with scores that would be indicative of strong silencing, said genes can
be reassessed with a second algorithm that is, for instance, less
stringent.

[0364]siRNA sequences identified using Formula VIII and Formula X (minus
sequences generated by Formula VIII) are contained within the sequence
listing. The data included in the sequence listing is described more
fully below. The sequences identified by Formula VIII and Formula X that
are disclosed in the sequence listing may be used in gene silencing
applications.

[0365]It should be noted that for Formulas VIII, IX, and X all of the
aforementioned criteria are identified as positions on the sense strand
when oriented in the 5' to 3' direction as they are identified in
connection with Formulas I-VII unless otherwise specified.

[0366]Formulas I-X, may be used to select or to evaluate one, or more than
one, siRNA in order to optimize silencing. Preferably, at least two
optimized siRNAs that have been selected according to at least one of
these formulas are used to silence a gene, more preferably at least three
and most preferably at least four. The siRNAs may be used individually or
together in a pool or kit. Further, they may be applied to a cell
simultaneously or separately. Preferably, the at least two siRNAs are
applied simultaneously. Pools are particularly beneficial for many
research applications. However, for therapeutics, it may be more
desirable to employ a single hyperfunctional siRNA as described elsewhere
in this application.

[0367]When planning to conduct gene silencing, and it is necessary to
choose between two or more siRNAs, one should do so by comparing the
relative values when the siRNA are subjected to one of the formulas
above. In general a higher scored siRNA should be used.

[0368]Useful applications include, but are not limited to, target
validation, gene functional analysis, research and drug discovery, gene
therapy and therapeutics. Methods for using siRNA in these applications
are well known to persons of skill in the art.

[0369]Because the ability of siRNA to function is dependent on the
sequence of the RNA and not the species into which it is introduced, the
present invention is applicable across a broad range of species,
including but not limited to all mammalian species, such as humans, dogs,
horses, cats, cows, mice, hamsters, chimpanzees and gorillas, as well as
other species and organisms such as bacteria, viruses, insects, plants
and C. elegans.

[0370]The present invention is also applicable for use for silencing a
broad range of genes, including but not limited to the roughly 45,000
genes of a human genome, and has particular relevance in cases where
those genes are associated with diseases such as diabetes, Alzheimer's,
cancer, as well as all genes in the genomes of the aforementioned
organisms.

[0371]The siRNA selected according to the aforementioned criteria or one
of the aforementioned algorithms are also, for example, useful in the
simultaneous screening and functional analysis of multiple genes and gene
families using high throughput strategies, as well as in direct gene
suppression or silencing.

Development of the Algorithms

[0372]To identify siRNA sequence features that promote functionality and
to quantify the importance of certain currently accepted conventional
factors--such as G/C content and target site accessibility--the inventors
synthesized an siRNA panel consisting of 270 siRNAs targeting three
genes, Human Cyclophilin, Firefly Luciferase, and Human DBI. In all three
cases, siRNAs were directed against specific regions of each gene. For
Human Cyclophilin and Firefly Luciferase, ninety siRNAs were directed
against a 199 by segment of each respective mRNA. For DBI, 90 siRNAs were
directed against a smaller, 109 base pair region of the mRNA. The
sequences to which the siRNAs were directed are provided below.

[0373]It should be noted that in certain sequences, "t" is present. This
is because many databases contain information in this manner. However,
the t denotes a uracil residue in mRNA and siRNA. Any algorithm will,
unless otherwise specified, process a t in a sequence as a u.

[0375]The set of duplexes was analyzed to identify correlations between
siRNA functionality and other biophysical or thermodynamic properties.
When the siRNA panel was analyzed in functional and non-functional
subgroups, certain nucleotides were much more abundant at certain
positions in functional or non-functional groups. More specifically, the
frequency of each nucleotide at each position in highly functional siRNA
duplexes was compared with that of nonfunctional duplexes in order to
assess the preference for or against any given nucleotide at every
position. These analyses were used to determine important criteria to be
included in the siRNA algorithms (Formulas VIII, IX, and X).

[0376]The data set was also analyzed for distinguishing biophysical
properties of siRNAs in the functional group, such as optimal percent of
GC content, propensity for internal structures and regional thermodynamic
stability. Of the presented criteria, several are involved in duplex
recognition, RISC activation/duplex unwinding, and target cleavage
catalysis.

[0377]The original data set that was the source of the statistically
derived criteria is shown in FIG. 2. Additionally, this figure shows that
random selection yields siRNA duplexes with unpredictable and widely
varying silencing potencies as measured in tissue culture using HEK293
cells. In the figure, duplexes are plotted such that each x-axis
tick-mark represents an individual siRNA, with each subsequent siRNA
differing in target position by two nucleotides for Human Cyclophilin B
and Firefly Luciferase, and by one nucleotide for Human DBI. Furthermore,
the y-axis denotes the level of target expression remaining after
transfection of the duplex into cells and subsequent silencing of the
target.

[0378]siRNA identified and optimized in this document work equally well in
a wide range of cell types. FIG. 3a shows the evaluation of thirty siRNAs
targeting the DBI gene in three cell lines derived from different
tissues. Each DBI siRNA displays very similar functionality in HEK293
(ATCC, CRL-1573, human embryonic kidney), HeLa (ATCC, CCL-2, cervical
epithelial adenocarcinoma) and DU145 (HTB-81, prostate) cells as
determined by the B-DNA assay. Thus, siRNA functionality is determined by
the primary sequence of the siRNA and not by the intracellular
environment. Additionally, it should be noted that although the present
invention provides for a determination of the functionality of siRNA for
a given target, the same siRNA may silence more than one gene. For
example, the complementary sequence of the silencing siRNA may be present
in more than one gene. Accordingly, in these circumstances, it may be
desirable not to use the siRNA with highest SMARTSCORE®, or siRNA
ranking. In such circumstances, it may be desirable to use the siRNA with
the next highest SMARTSCORE®, or siRNA ranking.

[0379]To determine the relevance of G/C content in siRNA function, the G/C
content of each duplex in the panel was calculated and the functional
classes of siRNAs (<F50, ≧F50, ≧F80, ≧F95 where F
refers to the percent gene silencing) were sorted accordingly. The
majority of the highly-functional siRNAs (≧F95) fell within the
G/C content range of 36%-52% (FIG. 3B). Twice as many non-functional
(<F50) duplexes fell within the high G/C content groups (>57% GC
content) compared to the 36%-52% group. The group with extremely low GC
content (26% or less) contained a higher proportion of non-functional
siRNAs and no highly-functional siRNAs. The G/C content range of 30%-52%
was therefore selected as Criterion I for siRNA functionality, consistent
with the observation that a G/C range 30%-70% promotes efficient RNAi
targeting. Application of this criterion alone provided only a marginal
increase in the probability of selecting functional siRNAs from the
panel: selection of F50 and F95 siRNAs was improved by 3.6% and 2.2%,
respectively. The siRNA panel presented here permitted a more systematic
analysis and quantification of the importance of this criterion than that
used previously.

[0380]A relative measure of local internal stability is the A/U base pair
(bp) content; therefore, the frequency of A/U by was determined for each
of the five terminal positions of the duplex (5' sense (S)/5' antisense
(AS)) of all siRNAs in the panel. Duplexes were then categorized by the
number of A/U by in positions 1-5 and 15-19 of the sense strand. The
thermodynamic flexibility of the duplex 5'-end (positions 1-5; S) did not
appear to correlate appreciably with silencing potency, while that of the
3'-end (positions 15-19; S) correlated with efficient silencing. No
duplexes lacking A/U by in positions 15-19 were functional. The presence
of one A/U by in this region conferred some degree of functionality, but
the presence of three or more A/Us was preferable and therefore defined
as Criterion II. When applied to the test panel, only a marginal increase
in the probability of functional siRNA selection was achieved: a 1.8% and
2.3% increase for F50 and F95 duplexes, respectively (Table IV).

[0381]The complementary strands of siRNAs that contain internal repeats or
palindromes may form internal fold-back structures. These hairpin-like
structures exist in equilibrium with the duplexed form effectively
reducing the concentration of functional duplexes. The propensity to form
internal hairpins and their relative stability can be estimated by
predicted melting temperatures. High Tm reflects a tendency to form
hairpin structures. Lower Tm values indicate a lesser tendency to form
hairpins. When the functional classes of siRNAs were sorted by Tm
(FIG. 3c), the following trends were identified: duplexes lacking stable
internal repeats were the most potent silencers (no F95 duplex with
predicted hairpin structure Tm>60° C.). In contrast, about
60% of the duplexes in the groups having internal hairpins with
calculated Tm values less than 20° C. were F80. Thus, the
stability of internal repeats is inversely proportional to the silencing
effect and defines Criterion III (predicted hairpin structure
Tm≦20° C.).

Sequence-Based Determinants of siRNA Functionality

[0382]When the siRNA panel was sorted into functional and non-functional
groups, the frequency of a specific nucleotide at each position in a
functional siRNA duplex was compared with that of a nonfunctional duplex
in order to assess the preference for or against a certain nucleotide.
FIG. 4 shows the results of these queries and the subsequent resorting of
the data set (from FIG. 2). The data is separated into two sets: those
duplexes that meet the criteria, a specific nucleotide in a certain
position--grouped on the left (Selected) and those that do not--grouped
on the right (Eliminated). The duplexes are further sorted from most
functional to least functional with the y-axis of FIG. 4a-e representing
the % expression i.e., the amount of silencing that is elicited by the
duplex (Note: each position on the X-axis represents a different duplex).
Statistical analysis revealed correlations between silencing and several
sequence-related properties of siRNAs. FIG. 4 and Table IV show
quantitative analysis for the following five sequence-related properties
of siRNA: (A) an A at position 19 of the sense strand; (B) an A at
position 3 of the sense strand; (C) a U at position 10 of the sense
strand; (D) a base other than G at position 13 of the sense strand; and
(E) a base other than C at position 19 of the sense strand.

[0383]When the siRNAs in the panel were evaluated for the presence of an A
at position 19 of the sense strand, the percentage of non-functional
duplexes decreased from 20% to 11.8%, and the percentage of F95 duplexes
increased from 21.7% to 29.4% (Table IV). Thus, the presence of an A in
this position defined Criterion IV.

[0384]Another sequence-related property correlated with silencing was the
presence of an A in position 3 of the sense strand (FIG. 4B). Of the
siRNAs with A3, 34.4% were F95, compared with 21.7% randomly selected
siRNAs. The presence of a U base in position 10 of the sense strand
exhibited an even greater impact (FIG. 4c). Of the duplexes in this
group, 41.7% were F95. These properties became criteria V and VI,
respectively.

[0385]Two negative sequence-related criteria that were identified also
appear on FIG. 4. The absence of a G at position 13 of the sense strand,
conferred a marginal increase in selecting functional duplexes (FIG. 4D).
Similarly, lack of a C at position 19 of the sense strand also correlated
with functionality (FIG. 4E). Thus, among functional duplexes, position
19 was most likely occupied by A, and rarely occupied by C. These rules
were defined as criteria VII and VIII, respectively.

[0386]Application of each criterion individually provided marginal but
statistically significant increases in the probability of selecting a
potent siRNA. Although the results were informative, the inventors sought
to maximize potency and therefore consider multiple criteria or
parameters. Optimization is particularly important when developing
therapeutics. Interestingly, the probability of selecting a functional
siRNA based on each thermodynamic criteria was 2%-4% higher than random,
but 4%-8% higher for the sequence-related determinates. Presumably, these
sequence-related increases reflect the complexity of the RNAi mechanism
and the multitude of protein-RNA interactions that are involved in
RNAi-mediated silencing.

[0387]In an effort to improve selection further, all identified criteria,
including but not limited to those listed in Table IV were combined into
the algorithms embodied in Formula VIII, Formula IX, and Formula X. Each
siRNA was then assigned a score (referred to as a SMARTSCORE®, or
siRNA ranking) according to the values derived from the formulas.
Duplexes that scored higher than 0 or -20 (unadjusted), for Formulas VIII
and IX, respectively, effectively selected a set of functional siRNAs and
excluded all non-functional siRNAs. Conversely, all duplexes scoring
lower than 0 and -20 (minus 20) according to formulas VIII and IX,
respectively, contained some functional siRNAs but included all
non-functional siRNAs. A graphical representation of this selection is
shown in FIG. 5. It should be noted that the scores derived from the
algorithm can also be provided as "adjusted" scores. To convert Formula
VIII unadjusted scores into adjusted scores it is necessary to use the
following equation:

(160+unadjusted score)/2.25

[0388]When this takes place, an unadjusted score of "0" (zero) is
converted to 75. Similarly, unadjusted scores for Formula X can be
converted to adjusted scores. In this instance, the following equation is
applied:

(228+unadjusted score)/3.56

[0389]When these manipulations take place, an unadjusted score of 38 is
converted to an adjusted score of 75.

[0390]The methods for obtaining the seven criteria embodied in Table IV
are illustrative of the results of the process used to develop the
information for Formulas VIII, IX, and X. Thus similar techniques were
used to establish the other variables and their multipliers. As described
above, basic statistical methods were use to determine the relative
values for these multipliers.

[0391]To determine the value for "Improvement over Random" the difference
in the frequency of a given attribute (e.g., GC content, base preference)
at a particular position is determined between individual functional
groups (e.g., <F50) and the total siRNA population studied (e.g., 270
siRNA molecules selected randomly). Thus, for instance, in Criterion I
(30%-52% GC content) members of the <F50 group were observed to have
GC contents between 30-52% in 16.4% of the cases. In contrast, the total
group of 270 siRNAs had GC contents in this range, 20% of the time. Thus
for this particular attribute, there is a small negative correlation
between 30%-52% GC content and this functional group (i.e.,
16.4%-20%=-3.6%). Similarly, for Criterion VI, (a "U" at position 10 of
the sense strand), the >F95 group contained a "U" at this position
41.7% of the time. In contrast, the total group of 270 siRNAs had a "U"
at this position 21.7% of the time, thus the improvement over random is
calculated to be 20% (or 41.7%-21.7%).

Identifying the Average Internal Stability Profile of Strong siRNA

[0392]In order to identify an internal stability profile that is
characteristic of strong siRNA, 270 different siRNAs derived from the
cyclophilin B, the diazepam binding inhibitor (DBI), and the luciferase
gene were individually transfected into HEK293 cells and tested for their
ability to induce RNAi of the respective gene. Based on their performance
in the in vivo assay, the sequences were then subdivided into three
groups, (i) >95% silencing; (ii) 80-95% silencing; and (iii) less than
50% silencing. Sequences exhibiting 51-84% silencing were eliminated from
further consideration to reduce the difficulties in identifying relevant
thermodynamic patterns.

[0393]Following the division of siRNA into three groups, a statistical
analysis was performed on each member of each group to determine the
average internal stability profile (AISP) of the siRNA. To accomplish
this the Oligo 5.0 Primer Analysis Software and other related statistical
packages (e.g., Excel) were exploited to determine the internal stability
of pentamers using the nearest neighbor method described by Freier et
al., (1986) Improved free-energy parameters for predictions of RNA duplex
stability, Proc Natl. Acad. Sci. USA 83(24): 9373-7. Values for each
group at each position were then averaged, and the resulting data were
graphed on a linear coordinate system with the Y-axis expressing the
ΔG (free energy) values in kcal/mole and the X-axis identifying the
position of the base relative to the 5' end.

[0394]The results of the analysis identified multiple key regions in siRNA
molecules that were critical for successful gene silencing. At the
3'-most end of the sense strand (5'antisense), highly functional siRNA
(>95% gene silencing, see FIG. 6a, >F95) have a low internal
stability (AISP of position 19=˜-7.6 kcal/mol). In contrast
low-efficiency siRNA (i.e., those exhibiting less than 50% silencing,
<F50) display a distinctly different profile, having high ΔG
values (˜-8.4 kcal/mol) for the same position. Moving in a 5'
(sense strand) direction, the internal stability of highly efficient
siRNA rises (position 12=˜-8.3 kcal/mole) and then drops again
(position 7=˜-7.7 kcal/mol) before leveling off at a value of
approximately -8.1 kcal/mol for the 5' terminus. siRNA with poor
silencing capabilities show a distinctly different profile. While the
AISP value at position 12 is nearly identical with that of strong siRNAs,
the values at positions 7 and 8 rise considerably, peaking at a high of
˜-9.0 kcal/mol. In addition, at the 5' end of the molecule the AISP
profile of strong and weak siRNA differ dramatically. Unlike the
relatively strong values exhibited by siRNA in the >95% silencing
group, siRNAs that exhibit poor silencing activity have weak AISP values
(-7.6, -7.5, and -7.5 kcal/mol for positions 1, 2 and 3 respectively).

[0395]Overall the profiles of both strong and weak siRNAs form distinct
sinusoidal shapes that are roughly 180° out-of-phase with each
other. While these thermodynamic descriptions define the archetypal
profile of a strong siRNA, it will likely be the case that neither the
ΔG values given for key positions in the profile or the absolute
position of the profile along the Y-axis (i.e., the ΔG-axis) are
absolutes. Profiles that are shifted upward or downward (i.e., having on
an average, higher or lower values at every position) but retain the
relative shape and position of the profile along the X-axis can be
foreseen as being equally effective as the model profile described here.
Moreover, it is likely that siRNA that have strong or even stronger
gene-specific silencing effects might have exaggerated ΔG values
(either higher or lower) at key positions. Thus, for instance, it is
possible that the 5'-most position of the sense strand (position 19)
could have ΔG values of 7.4 kcal/mol or lower and still be a strong
siRNA if, for instance, a G-C→G-T/U mismatch were substituted at
position 19 and altered duplex stability. Similarly, position 12 and
position 7 could have values above 8.3 kcal/mol and below 7.7 kcal/mole,
respectively, without abating the silencing effectiveness of the
molecule. Thus, for instance, at position 12, a stabilizing chemical
modification (e.g., a chemical modification of the 2' position of the
sugar backbone) could be added that increases the average internal
stability at that position. Similarly, at position 7, mismatches similar
to those described previously could be introduced that would lower the
ΔG values at that position.

[0396]Lastly, it is important to note that while functional and
non-functional siRNA were originally defined as those molecules having
specific silencing properties, both broader or more limiting parameters
can be used to define these molecules. As used herein, unless otherwise
specified, "non-functional siRNA" are defined as those siRNA that induce
less than 50% (<50%) target silencing, "semi-functional siRNA" induce
50-79% target silencing, "functional siRNA" are molecules that induce
80-95% gene silencing, and "highly-functional siRNA" are molecules that
induce great than 95% gene silencing. These definitions are not intended
to be rigid and can vary depending upon the design and needs of the
application. For instance, it is possible that a researcher attempting to
map a gene to a chromosome using a functional assay, may identify an
siRNA that reduces gene activity by only 30%. While this level of gene
silencing may be "non-functional" for, e.g., therapeutic needs, it is
sufficient for gene mapping purposes and is, under these uses and
conditions, "functional." For these reasons, functional siRNA can be
defined as those molecules having greater than 10%, 20%, 30%, 40%, 50%,
60%, 70%, 80%, or 90% silencing capabilities at 100 nM transfection
conditions. Similarly, depending upon the needs of the study and/or
application, non-functional and semi-functional siRNA can be defined as
having different parameters. For instance, semi-functional siRNA can be
defined as being those molecules that induce 20%, 30%, 40%, 50%, 60%, or
70% silencing at 100 nM transfection conditions. Similarly,
non-functional siRNA can be defined as being those molecules that silence
gene expression by less than 70%, 60%, 50%, 40%, 30%, or less.
Nonetheless, unless otherwise stated, the descriptions stated in the
"Definitions" section of this text should be applied.

[0397]Functional attributes can be assigned to each of the key positions
in the AISP of strong siRNA. The low 5' (sense strand) AISP values of
strong siRNAs may be necessary for determining which end of the molecule
enters the RISC complex. In contrast, the high and low AISP values
observed in the central regions of the molecule may be critical for
siRNA-target mRNA interactions and product release, respectively.

[0398]If the AISP values described above accurately define the
thermodynamic parameters of strong siRNA, it would be expected that
similar patterns would be observed in strong siRNA isolated from nature.
Natural siRNAs exist in a harsh, RNase-rich environment and it can be
hypothesized that only those siRNA that exhibit heightened affinity for
RISC (i.e., siRNA that exhibit an average internal stability profile
similar to those observed in strong siRNA) would survive in an
intracellular environment. This hypothesis was tested using GFP-specific
siRNA isolated from N. benthamiana. Llave et al. (2002) Endogenous and
Silencing-Associated Small RNAs in Plants, The Plant Cell 14, 1605-1619,
introduced long double-stranded GFP-encoding RNA into plants and
subsequently re-isolated GFP-specific siRNA from the tissues. The AISP of
fifty-nine of these GFP-siRNA were determined, averaged, and subsequently
plotted alongside the AISP profile obtained from the cyclophilin
B/DBI/luciferase siRNA having >90% silencing properties (FIG. 6B).
Comparison of the two groups show that profiles are nearly identical.
This finding validates the information provided by the internal stability
profiles and demonstrates that: (1) the profile identified by analysis of
the cyclophilin B/DBI/luciferase siRNAs are not gene specific; and (2)
AISP values can be used to search for strong siRNAs in a variety of
species.

[0399]Both chemical modifications and base-pair mismatches can be
incorporated into siRNA to alter the duplex's AISP and functionality. For
instance, introduction of mismatches at positions 1 or 2 of the sense
strand destabilized the 5'end of the sense strand and increases the
functionality of the molecule (see Luc, FIG. 7). Similarly, addition of
2'-O-methyl groups to positions 1 and 2 of the sense strand can also
alter the AISP and (as a result) increase both the functionality of the
molecule and eliminate off-target effects that results from sense strand
homology with the unrelated targets (FIG. 8).

Rationale for Criteria in a Biological Context

[0400]The fate of siRNA in the RNAi pathway may be described in 5 major
steps: (1) duplex recognition and pre-RISC complex formation; (2)
ATP-dependent duplex unwinding/strand selection and RISC activation; (3)
mRNA target identification; (4) mRNA cleavage, and (5) product release
(FIG. 1). Given the level of nucleic acid-protein interactions at each
step, siRNA functionality is likely influenced by specific biophysical
and molecular properties that promote efficient interactions within the
context of the multi-component complexes. Indeed, the systematic analysis
of the siRNA test set identified multiple factors that correlate well
with functionality. When combined into a single algorithm, they proved to
be very effective in selecting active siRNAs.

[0401]The factors described here may also be predictive of key functional
associations important for each step in RNAi. For example, the potential
formation of internal hairpin structures correlated negatively with siRNA
functionality. Complementary strands with stable internal repeats are
more likely to exist as stable hairpins thus decreasing the effective
concentration of the functional duplex form. This suggests that the
duplex is the preferred conformation for initial pre-RISC association.
Indeed, although single complementary strands can induce gene silencing,
the effective concentration required is at least two orders of magnitude
higher than that of the duplex form.

[0402]siRNA-pre-RISC complex formation is followed by an ATP-dependent
duplex unwinding step and "activation" of the RISC. The siRNA
functionality was shown to correlate with overall low internal stability
of the duplex and low internal stability of the 3' sense end (or
differential internal stability of the 3' sense compare to the 5' sense
strand), which may reflect strand selection and entry into the RISC.
Overall duplex stability and low internal stability at the 3' end of the
sense strand were also correlated with siRNA functionality.
Interestingly, siRNAs with very high and very low overall stability
profiles correlate strongly with non-functional duplexes. One
interpretation is that high internal stability prevents efficient
unwinding while very low stability reduces siRNA target affinity and
subsequent mRNA cleavage by the RISC.

[0403]Several criteria describe base preferences at specific positions of
the sense strand and are even more intriguing when considering their
potential mechanistic roles in target recognition and mRNA cleavage. Base
preferences for A at position 19 of the sense strand but not C, are
particularly interesting because they reflect the same base preferences
observed for naturally occurring miRNA precursors. That is, among the
reported miRNA precursor sequences 75% contain a U at position 1 which
corresponds to an A in position 19 of the sense strand of siRNAs, while G
was under-represented in this same position for miRNA precursors. These
observations support the hypothesis that both miRNA precursors and siRNA
duplexes are processed by very similar if not identical protein
machinery. The functional interpretation of the predominance of a U/A
base pair is that it promotes flexibility at the 5'antisense ends of both
siRNA duplexes and miRNA precursors and facilitates efficient unwinding
and selective strand entrance into an activated RISC.

[0404]Among the criteria associated with base preferences that are likely
to influence mRNA cleavage or possibly product release, the preference
for U at position 10 of the sense strand exhibited the greatest impact,
enhancing the probability of selecting an F80 sequence by 13.3%.
Activated RISC preferentially cleaves target mRNA between nucleotides 10
and 11 relative to the 5' end of the complementary targeting strand.
Therefore, it may be that U, the preferred base for most
endoribonucleases, at this position supports more efficient cleavage.
Alternatively, a U/A by between the targeting siRNA strand and its
cognate target mRNA may create an optimal conformation for the
RISC-associated "slicing" activity.

Post Algorithm Filters

[0405]According to another embodiment, the output of any one of the
formulas previously listed can be filtered to remove or select for siRNAs
containing undesirable or desirable motifs or properties, respectively.
In one example, sequences identified by any of the formulas can be
filtered to remove any and all sequences that induce toxicity or cellular
stress. Introduction of an siRNA containing a toxic motif into a cell can
induce cellular stress and/or cell death (apoptosis) which in turn can
mislead researchers into associating a particular (e.g., nonessential)
gene with, e.g., an essential function. Alternatively, sequences
generated by any of the before mentioned formulas can be filtered to
identify and retain duplexes that contain toxic motifs. Such duplexes may
be valuable from a variety of perspectives including, for instance, uses
as therapeutic molecules. A variety of toxic motifs exist and can exert
their influence on the cell through RNAi and non-RNAi pathways. Examples
of toxic motifs are explained more fully in commonly assigned U.S.
Provisional Patent Application Ser. No. 60/538,874, entitled
"Identification of Toxic Sequences," filed Jan. 23, 2004. Briefly, toxic
motifs include A/G UUU A/G/U, G/C AAA G/C, and GCCA, or a complement of
any of the foregoing.

[0406]In another instance, sequences identified by any of the before
mentioned formulas can be filtered to identify duplexes that contain
motifs (or general properties) that provide serum stability or induce
serum instability. In one envisioned application of siRNA as therapeutic
molecules, duplexes targeting disease-associated genes will be introduced
into patients intravenously. As the half-life of single and double
stranded RNA in serum is short, post-algorithm filters designed to select
molecules that contain motifs that enhance duplex stability in the
presence of serum and/or (conversely) eliminate duplexes that contain
motifs that destabilize siRNA in the presence of serum, would be
beneficial.

[0407]In another instance, sequences identified by any of the before
mentioned formulas can be filtered to identify duplexes that are
hyperfunctional. Hyperfunctional sequences are defined as those sequences
that (1) induce greater than 95% silencing of a specific target when they
are transfected at subnanomolar concentrations (i.e., less than one
nanomolar); and/or (2) induce functional (or better) levels of silencing
for greater than 96 hours. Filters that identify hyperfunctional
molecules can vary widely. In one example, the top ten, twenty, thirty,
or forty siRNA can be assessed for the ability to silence a given target
at, e.g., concentrations of 1 nM and 0.5 nM to identify hyperfunctional
molecules.

Pooling

[0408]According to another embodiment, the present invention provides a
pool of at least two siRNAs, preferably in the form of a kit or
therapeutic reagent, wherein one strand of each of the siRNAs, the sense
strand comprises a sequence that is substantially similar to a sequence
within a target mRNA. The opposite strand, the antisense strand, will
preferably comprise a sequence that is substantially complementary to
that of the target mRNA. More preferably, one strand of each siRNA will
comprise a sequence that is identical to a sequence that is contained in
the target mRNA. Most preferably, each siRNA will be 19 base pairs in
length, and one strand of each of the siRNAs will be 100% complementary
to a portion of the target mRNA.

[0409]By increasing the number of siRNAs directed to a particular target
using a pool or kit, one is able both to increase the likelihood that at
least one siRNA with satisfactory functionality will be included, as well
as to benefit from additive or synergistic effects. Further, when two or
more siRNAs directed against a single gene do not have satisfactory
levels of functionality alone, if combined, they may satisfactorily
promote degradation of the target messenger RNA and successfully inhibit
translation. By including multiple siRNAs in the system, not only is the
probability of silencing increased, but the economics of operation are
also improved when compared to adding different siRNAs sequentially. This
effect is contrary to the conventional wisdom that the concurrent use of
multiple siRNA will negatively impact gene silencing (e.g., Holen, T. et
al. (2003) Similar behavior of single strand and double strand siRNAs
suggests they act through a common RNAi pathway. NAR 31: 2401-21407).

[0410]In fact, when two siRNAs were pooled together, 54% of the pools of
two siRNAs induced more than 95% gene silencing. Thus, a 2.5-fold
increase in the percentage of functionality was achieved by randomly
combining two siRNAs. Further, over 84% of pools containing two siRNAs
induced more than 80% gene silencing.

[0411]More preferably, the kit is comprised of at least three siRNAs,
wherein one strand of each siRNA comprises a sequence that is
substantially similar to a sequence of the target mRNA and the other
strand comprises a sequence that is substantially complementary to the
region of the target mRNA. As with the kit that comprises at least two
siRNAs, more preferably one strand will comprise a sequence that is
identical to a sequence that is contained in the mRNA and another strand
that is 100% complementary to a sequence that is contained in the mRNA.
During experiments, when three siRNAs were combined together, 60% of the
pools induced more than 95% gene silencing and 92% of the pools induced
more than 80% gene silencing.

[0412]Further, even more preferably, the kit is comprised of at least four
siRNAs, wherein one strand of each siRNA comprises a sequence that is
substantially similar to a region of the sequence of the target mRNA, and
the other strand comprises a sequence that is substantially complementary
to the region of the target mRNA. As with the kit or pool that comprises
at least two siRNAs, more preferably one strand of each of the siRNA
duplexes will comprise a sequence that is identical to a sequence that is
contained in the mRNA, and another strand that is 100% complementary to a
sequence that is contained in the mRNA.

[0413]Additionally, kits and pools with at least five, at least six, and
at least seven siRNAs may also be useful with the present invention. For
example, pools of five siRNA induced 95% gene silencing with 77%
probability and 80% silencing with 98.8% probability. Thus, pooling of
siRNAs together can result in the creation of a target-specific silencing
reagent with almost a 99% probability of being functional. The fact that
such high levels of success are achievable using such pools of siRNA,
enables one to dispense with costly and time-consuming target-specific
validation procedures.

[0414]For this embodiment, as well as the other aforementioned
embodiments, each of the siRNAs within a pool will preferably comprise
18-30 base pairs, more preferably 18-25 base pairs, and most preferably
19 base pairs. Within each siRNA, preferably at least 18 contiguous bases
of the antisense strand will be 100% complementary to the target mRNA.
More preferably, at least 19 contiguous bases of the antisense strand
will be 100% complementary to the target mRNA. Additionally, there may be
overhangs on either the sense strand or the antisense strand, and these
overhangs may be at either the 5' end or the 3' end of either of the
strands, for example there may be one or more overhangs of 1-6 bases.
When overhangs are present, they are not included in the calculation of
the number of base pairs. The two nucleotide 3' overhangs mimic natural
siRNAs and are commonly used but are not essential. Preferably, the
overhangs should consist of two nucleotides, most often dTdT or UU at the
3' end of the sense and antisense strand that are not complementary to
the target sequence. The siRNAs may be produced by any method that is now
known or that comes to be known for synthesizing double stranded RNA that
one skilled in the art would appreciate would be useful in the present
invention. Preferably, the siRNAs will be produced by Dharmacon's
proprietary ACE® technology. However, other methods for synthesizing
siRNAs are well known to persons skilled in the art and include, but are
not limited to, any chemical synthesis of RNA oligonucleotides, ligation
of shorter oligonucleotides, in vitro transcription of RNA
oligonucleotides, the use of vectors for expression within cells,
recombinant Dicer products and PCR products.

[0415]The siRNA duplexes within the aforementioned pools of siRNAs may
correspond to overlapping sequences within a particular mRNA, or
non-overlapping sequences of the mRNA. However, preferably they
correspond to non-overlapping sequences. Further, each siRNA may be
selected randomly, or one or more of the siRNA may be selected according
to the criteria discussed above for maximizing the effectiveness of
siRNA.

[0416]Included in the definition of siRNAs are siRNAs that contain
substituted and/or labeled nucleotides that may, for example, be labeled
by radioactivity, fluorescence or mass. The most common substitutions are
at the 2' position of the ribose sugar, where moieties such as H
(hydrogen) F, NH3, OCH3 and other O-alkyl, alkenyl, alkynyl,
and orthoesters, may be substituted, or in the phosphorous backbone,
where sulfur, amines or hydrocarbons may be substituted for the bridging
of non-bridging atoms in the phosphodiester bond. Examples of modified
siRNAs are explained more fully in commonly assigned U.S. patent
application Ser. No. 10/613,077, filed Jul. 1, 2003.

[0417]Additionally, as noted above, the cell type into which the siRNA is
introduced may affect the ability of the siRNA to enter the cell;
however, it does not appear to affect the ability of the siRNA to
function once it enters the cell. Methods for introducing double-stranded
RNA into various cell types are well known to persons skilled in the art.

[0418]As persons skilled in the art are aware, in certain species, the
presence of proteins such as RdRP, the RNA-dependent RNA polymerase, may
catalytically enhance the activity of the siRNA. For example, RdRP
propagates the RNAi effect in C. elegans and other non-mammalian
organisms. In fact, in organisms that contain these proteins, the siRNA
may be inherited. Two other proteins that are well studied and known to
be a part of the machinery are members of the Argonaute family and Dicer,
as well as their homologues. There is also initial evidence that the RISC
complex might be associated with the ribosome so the more efficiently
translated mRNAs will be more susceptible to silencing than others.

[0419]Another very important factor in the efficacy of siRNA is mRNA
localization. In general, only cytoplasmic mRNAs are considered to be
accessible to RNAi to any appreciable degree. However, appropriately
designed siRNAs, for example, siRNAs modified with internucleotide
linkages or 2'-O-methyl groups, may be able to cause silencing by acting
in the nucleus. Examples of these types of modifications are described in
commonly assigned U.S. patent application Ser. Nos. 10/431,027 and
10/613,077.

[0420]As described above, even when one selects at least two siRNAs at
random, the effectiveness of the two may be greater than one would
predict based on the effectiveness of two individual siRNAs. This
additive or synergistic effect is particularly noticeable as one
increases to at least three siRNAs, and even more noticeable as one moves
to at least four siRNAs. Surprisingly, the pooling of the non-functional
and semi-functional siRNAs, particularly more than five siRNAs, can lead
to a silencing mixture that is as effective if not more effective than
any one particular functional siRNA.

[0421]Within the kits of the present invention, preferably each siRNA will
be present in a concentration of between 0.001 and 200 μM, more
preferably between 0.01 and 200 nM, and most preferably between 0.1 and
10 nM.

[0422]In addition to preferably comprising at least four or five siRNAs,
the kits of the present invention will also preferably comprise a buffer
to keep the siRNA duplex stable. Persons skilled in the art are aware of
buffers suitable for keeping siRNA stable. For example, the buffer may be
comprised of 100 mM KCl, 30 mM HEPES-pH 7.5, and 1 mM MgCl2.
Alternatively, kits might contain complementary strands that contain any
one of a number of chemical modifications (e.g., a 2'-O-ACE) that protect
the agents from degradation by nucleases. In this instance, the user may
(or may not) remove the modifying protective group (e.g., deprotect)
before annealing the two complementary strands together.

[0423]By way of example, the kits may be organized such that pools of
siRNA duplexes are provided on an array or microarray of wells or drops
for a particular gene set or for unrelated genes. The array may, for
example, be in 96 wells, 384 wells or 1284 wells arrayed in a plastic
plate or on a glass slide using techniques now known or that come to be
known to persons skilled in the art. Within an array, preferably there
will be controls such as functional anti-lamin A/C, cyclophilin and two
siRNA duplexes that are not specific to the gene of interest.

[0424]In order to ensure stability of the siRNA pools prior to usage, they
may be retained in lyophilized form at minus twenty degrees (-20°
C.) until they are ready for use. Prior to usage, they should be
resuspended; however, even once resuspended, for example, in the
aforementioned buffer, they should be kept at minus twenty degrees,
(-20° C.) until used. The aforementioned buffer, prior to use, may
be stored at approximately 4° C. or room temperature. Effective
temperatures at which to conduct transfections are well known to persons
skilled in the art and include for example, room temperature.

[0425]The kits may be applied either in vivo or in vitro. Preferably, the
siRNA of the pools or kits is applied to a cell through transfection,
employing standard transfection protocols. These methods are well known
to persons skilled in the art and include the use of lipid-based
carriers, electroporation, cationic carriers, and microinjection.
Further, one could apply the present invention by synthesizing equivalent
DNA sequences (either as two separate, complementary strands, or as
hairpin molecules) instead of siRNA sequences and introducing them into
cells through vectors. Once in the cells, the cloned DNA could be
transcribed, thereby forcing the cells to generate the siRNA. Examples of
vectors suitable for use with the present application include but are not
limited to the standard transient expression vectors, adenoviruses,
retroviruses, lentivirus-based vectors, as well as other traditional
expression vectors. Any vector that has an adequate siRNA expression and
procession module may be used. Furthermore, certain chemical
modifications to siRNAs, including but not limited to conjugations to
other molecules, may be used to facilitate delivery. For certain
applications it may be preferable to deliver molecules without
transfection by simply formulating in a physiological acceptable
solution.

[0426]This embodiment may be used in connection with any of the
aforementioned embodiments. Accordingly, the sequences within any pool
may be selected by rational design.

Multigene Silencing

[0427]In addition to developing kits that contain multiple siRNA directed
against a single gene, another embodiment includes the use of multiple
siRNA targeting multiple genes. Multiple genes may be targeted through
the use of high- or hyper-functional siRNA. High- or hyper-functional
siRNA that exhibit increased potency, require lower concentrations to
induce desired phenotypic (and thus therapeutic) effects. This
circumvents RISC saturation. It therefore reasons that if lower
concentrations of a single siRNA are needed for knockout or knockdown
expression of one gene, then the remaining (uncomplexed) RISC will be
free and available to interact with siRNA directed against two, three,
four, or more, genes. Thus in this embodiment, the authors describe the
use of highly functional or hyper-functional siRNA to knock out three
separate genes. More preferably, such reagents could be combined to
knockout four distinct genes. Even more preferably, highly functional or
hyperfunctional siRNA could be used to knock out five distinct genes.
Most preferably, siRNA of this type could be used to knockout or
knockdown the expression of six or more genes.

Hyperfunctional siRNA

[0428]The term hyperfunctional siRNA (hf-siRNA) describes a subset of the
siRNA population that induces RNAi in cells at low- or sub-nanomolar
concentrations for extended periods of time. These traits, heightened
potency and extended longevity of the RNAi phenotype, are highly
attractive from a therapeutic standpoint. Agents having higher potency
require lesser amounts of the molecule to achieve the desired
physiological response, thus reducing the probability of side effects due
to "off-target" interference. In addition to the potential therapeutic
benefits associated with hyperfunctional siRNA, hf-siRNA are also
desirable from an economic perspective. Hyperfunctional siRNA may cost
less on a per-treatment basis, thus reducing overall expenditures to both
the manufacturer and the consumer.

[0429]Identification of hyperfunctional siRNA involves multiple steps that
are designed to examine an individual siRNA agent's concentration- and/or
longevity-profiles. In one non-limiting example, a population of siRNA
directed against a single gene are first analyzed using the previously
described algorithm (Formula VIII). Individual siRNA are then introduced
into a test cell line and assessed for the ability to degrade the target
mRNA. It is important to note that when performing this step it is not
necessary to test all of the siRNA. Instead, it is sufficient to test
only those siRNA having the highest SMARTSCORES®, or siRNA ranking
(i.e., SMARTSCORES®, or siRNA ranking >-10). Subsequently, the gene
silencing data is plotted against the SMARTSCORES®, or siRNA rankings
(see FIG. 9). siRNA that (1) induce a high degree of gene silencing
(i.e., they induce greater than 80% gene knockdown) and (2) have superior
SMARTSCORES® (i.e., a SMARTSCORE®, or siRNA ranking, of >-10,
suggesting a desirable average internal stability profile) are selected
for further investigations designed to better understand the molecule's
potency and longevity. In one, non-limiting study dedicated to
understanding a molecule's potency, an siRNA is introduced into one (or
more) cell types in increasingly diminishing concentrations (e.g.,
3.0→0.3 nM). Subsequently, the level of gene silencing induced by
each concentration is examined and siRNA that exhibit hyperfunctional
potency (i.e., those that induce 80% silencing or greater at, e.g.,
picomolar concentrations) are identified. In a second study, the
longevity profiles of siRNA having high (>-10) SMARTSCORES®, or
siRNA rankings and greater than 80% silencing are examined. In one
non-limiting example of how this is achieved, siRNA are introduced into a
test cell line and the levels of RNAi are measured over an extended
period of time (e.g., 24-168 hrs). siRNAs that exhibit strong RNA
interference patterns (i.e., >80% interference) for periods of time
greater than, e.g., 120 hours, are thus identified. Studies similar to
those described above can be performed on any and all of the >106
siRNA included in this document to further define the most functional
molecule for any given gene. Molecules possessing one or both properties
(extended longevity and heightened potency) are labeled "hyperfunctional
siRNA," and earmarked as candidates for future therapeutic studies.

[0430]While the example(s) given above describe one means by which
hyperfunctional siRNA can be isolated, neither the assays themselves nor
the selection parameters used are rigid and can vary with each family of
siRNA. Families of siRNA include siRNAs directed against a single gene,
or directed against a related family of genes.

[0431]The highest quality siRNA achievable for any given gene may vary
considerably. Thus, for example, in the case of one gene (gene X),
rigorous studies such as those described above may enable the
identification of an siRNA that, at picomolar concentrations, induces
99.sup.+% silencing for a period of 10 days. Yet identical studies of a
second gene (gene Y) may yield an siRNA that at high nanomolar
concentrations (e.g., 100 nM) induces only 75% silencing for a period of
2 days. Both molecules represent the very optimum siRNA for their
respective gene targets and therefore are designated "hyperfunctional."
Yet due to a variety of factors including but not limited to target
concentration, siRNA stability, cell type, off-target interference, and
others, equivalent levels of potency and longevity are not achievable.
Thus, for these reasons, the parameters described in the before mentioned
assays can vary. While the initial screen selected siRNA that had
SMARTSCORES® above -10 and a gene silencing capability of greater than
80%, selections that have stronger (or weaker) parameters can be
implemented. Similarly, in the subsequent studies designed to identify
molecules with high potency and longevity, the desired cutoff criteria
(i.e., the lowest concentration that induces a desirable level of
interference, or the longest period of time that interference can be
observed) can vary. The experimentation subsequent to application of the
rational criteria of this application is significantly reduced where one
is trying to obtain a suitable hyperfunctional siRNA for, for example,
therapeutic use. When, for example, the additional experimentation of the
type described herein is applied by one skilled in the art with this
disclosure in hand, a hyperfunctional siRNA is readily identified.

[0432]The siRNA may be introduced into a cell by any method that is now
known or that comes to be known and that from reading this disclosure,
persons skilled in the art would determine would be useful in connection
with the present invention in enabling siRNA to cross the cellular
membrane. These methods include, but are not limited to, any manner of
transfection, such as, for example, transfection employing DEAE-Dextran,
calcium phosphate, cationic lipids/liposomes, micelles, manipulation of
pressure, microinjection, electroporation, immunoporation, use of vectors
such as viruses, plasmids, cosmids, bacteriophages, cell fusions, and
coupling of the polynucleotides to specific conjugates or ligands such as
antibodies, antigens, or receptors, passive introduction, adding moieties
to the siRNA that facilitate its uptake, and the like.

[0433]Having described the invention with a degree of particularity,
examples will now be provided. These examples are not intended to and
should not be construed to limit the scope of the claims in any way.

Examples

General Techniques and Nomenclature

[0434]siRNA nomenclature. All siRNA duplexes are referred to by sense
strand. The first nucleotide of the 5'-end of the sense strand is
position 1, which corresponds to position 19 of the antisense strand for
a 19-mer. In most cases, to compare results from different experiments,
silencing was determined by measuring specific transcript mRNA levels or
enzymatic activity associated with specific transcript levels, 24 hours
post-transfection, with siRNA concentrations held constant at 100 nM. For
all experiments, unless otherwise specified, transfection efficiency was
ensured to be over 95%, and no detectable cellular toxicity was observed.
The following system of nomenclature was used to compare and report
siRNA-silencing functionality: "F" followed by the degree of minimal
knockdown. For example, F50 signifies at least 50% knockdown, F80 means
at least 80%, and so forth. For this study, all sub-F50 siRNAs were
considered non-functional.

[0435]Cell culture and transfection. 96-well plates are coated with 50
μl of 50 mg/ml poly-L-lysine (Sigma) for 1 hr, and then washed
3× with distilled water before being dried for 20 min. HEK293 cells
or HEK293Lucs or any other cell type of interest are released from their
solid support by trypsinization, diluted to 3.5×105 cells/ml,
followed by the addition of 100 μL of cells/well. Plates are then
incubated overnight at 37° C., 5% CO2. Transfection
procedures can vary widely depending on the cell type and transfection
reagents. In one non-limiting example, a transfection mixture consisting
of 2 mL Opti-MEM I (Gibco-BRL), 80 μl Lipofectamine 2000 (Invitrogen),
15 μL SUPERNasin at 20 U/μl (Ambion), and 1.5 μl of reporter
gene plasmid at 1 μg/μl is prepared in 5-ml polystyrene round
bottom tubes. One hundred μl of transfection reagent is then combined
with 100 μl of siRNAs in polystyrene deep-well titer plates (Beckman)
and incubated for 20 to 30 min at room temperature. Five hundred and
fifty microliters of Opti-MEM is then added to each well to bring the
final siRNA concentration to 100 nM. Plates are then sealed with parafilm
and mixed. Media is removed from HEK293 cells and replaced with 95 μl
of transfection mixture. Cells are incubated overnight at 37° C.,
5% CO2.

[0436]Quantification of gene knockdown. A variety of quantification
procedures can be used to measure the level of silencing induced by siRNA
or siRNA pools. In one non-limiting example: to measure mRNA levels 24
hrs post-transfection, QuantiGene branched-DNA (bDNA) kits (Bayer) (Wang,
et al, Regulation of insulin preRNA splicing by glucose. Proc. Natl.
Acad. Sci. USA 1997, 94:4360.) are used according to manufacturer
instructions. To measure luciferase activity, media is removed from
HEK293 cells 24 hrs post-transfection, and 50 μl of Steady-GLO reagent
(Promega) is added. After 5 minutes, plates are analyzed on a plate
reader.

Example I

Sequences Used to Develop the Algorithm

[0437]Anti-Firefly and anti-Cyclophilin siRNAs panels (FIG. 5a, b) sorted
according to using Formula VIII predicted values. All siRNAs scoring more
than 0 (formula VIII) and more then 20 (formula IX) are fully functional.
All ninety sequences for each gene (and DBI) appear below in Table III.

Validation of the Algorithm Using DBI, Luciferase, PLK, EGFR, and SEAP

[0438]The algorithm (Formula VIII) identified siRNAs for five genes, human
DBI, firefly luciferase (fLuc), renilla luciferase (rLuc), human PLK, and
human secreted alkaline phosphatase (SEAP). Four individual siRNAs were
selected on the basis of their SMARTSCORES® derived by analysis of
their sequence using Formula VIII (all of the siRNAs would be selected
with Formula IX as well) and analyzed for their ability to silence their
targets' expression. In addition to the scoring, a BLAST search was
conducted for each siRNA. To minimize the potential for off-target
silencing effects, only those target sequences with more than three
mismatches against un-related sequences were selected. Semizarov, et al.
(2003) Specificity of short interfering RNA determined through gene
expression signatures, Proc. Natl. Acad. Sci. USA, 100:6347. These
duplexes were analyzed individually and in pools of 4 and compared with
several siRNAs that were randomly selected. The functionality was
measured as a percentage of targeted gene knockdown as compared to
controls. All siRNAs were transfected as described by the methods above
at 100 nM concentration into HEK293 using Lipofectamine 2000. The level
of the targeted gene expression was evaluated by B-DNA as described above
and normalized to the non-specific control. FIG. 10 shows that the siRNAs
selected by the algorithm disclosed herein were significantly more potent
than randomly selected siRNAs. The algorithm increased the chances of
identifying an F50 siRNA from 48% to 91%, and an F80 siRNA from 13% to
57%. In addition, pools of SMART siRNA silence the selected target better
than randomly selected pools (see FIG. 10F).

Example III

Validation of the Algorithm Using Genes Involved in Clathrin-Dependent
Endocytosis

[0439]Components of clathrin-mediated endocytosis pathway are key to
modulating intracellular signaling and play important roles in disease.
Chromosomal rearrangements that result in fusion transcripts between the
Mixed-Lineage Leukemia gene (MLL) and CALM (clathrin assembly lymphoid
myeloid leukemia gene) are believed to play a role in leukemogenesis.
Similarly, disruptions in Rab7 and Rab9, as well as HIP1
(Huntingtin-interacting protein), genes that are believed to be involved
in endocytosis, are potentially responsible for ailments resulting in
lipid storage, and neuronal diseases, respectively. For these reasons,
siRNA directed against clathrin and other genes involved in the
clathrin-mediated endocytotic pathway are potentially important research
and therapeutic tools.

[0441]For each gene, four siRNAs duplexes with the highest scores were
selected and a BLAST search was conducted for each of them using the
Human EST database. In order to minimize the potential for off-target
silencing effects, only those sequences with more than three mismatches
against un-related sequences were used. All duplexes were synthesized at
Dharmacon, Inc. as 21-mers with 3'-UU overhangs using a modified method
of 2'-ACE chemistry, Scaringe (2000) Advanced 5'-silyl-2'-orthoester
approach to RNA oligonucleotide synthesis, Methods Enzymol. 317:3, and
the antisense strand was chemically phosphorylated to insure maximized
activity.

[0442]HeLa cells were grown in Dulbecco's modified Eagle's medium (DMEM)
containing 10% fetal bovine serum, antibiotics and glutamine. siRNA
duplexes were resuspended in 1× siRNA Universal buffer (Dharmacon,
Inc.) to 20 μM prior to transfection. HeLa cells in 12-well plates
were transfected twice with 4 μl of 20 μM siRNA duplex in 3 μl
Lipofectamine 2000 reagent (Invitrogen, Carlsbad, Calif., USA) at 24-hour
intervals. For the transfections in which 2 or 3 siRNA duplexes were
included, the amount of each duplex was decreased, so that the total
amount was the same as in transfections with single siRNAs. Cells were
plated into normal culture medium 12 hours prior to experiments, and
protein levels were measured 2 or 4 days after the first transfection.

[0443]Equal amounts of lysates were resolved by electrophoresis, blotted,
and stained with the antibody specific to targeted protein, as well as
antibodies specific to unrelated proteins, PP1 phosphatase and Tsg101
(not shown). The cells were lysed in Triton X-100/glycerol solubilization
buffer as described previously. Tebar, Bohlander, & Sorkin (1999)
Clathrin Assembly Lymphoid Myeloid Leukemia (CALM) Protein: Localization
in Endocytic-coated Pits, Interactions with Clathrin, and the Impact of
Overexpression on Clathrin-mediated Traffic, Mol. Biol. Cell, 10:2687.
Cell lysates were electrophoresed, transferred to nitrocellulose
membranes, and Western blotting was performed with several antibodies
followed by detection using enhanced chemiluminescence system (Pierce,
Inc). Several x-ray films were analyzed to determine the linear range of
the chemiluminescence signals, and the quantifications were performed
using densitometry and AlphaImager v5.5 software (Alpha Innotech
Corporation). In experiments with Eps15R-targeted siRNAs, cell lysates
were subjected to immunoprecipitation with Ab860, and Eps15R was detected
in immunoprecipitates by Western blotting as described above.

[0445]FIG. 11 demonstrates the in vivo functionality of 48 individual
siRNAs, selected using Formula VIII (most of them will meet the criteria
incorporated by Formula IX as well) targeting 12 genes. Various cell
lines were transfected with siRNA duplexes (Dup1-4) or pools of siRNA
duplexes (Pool), and the cells were lysed 3 days after transfection with
the exception of CALM (2 days) and β2 (4 days).

[0446]Note a β1-adaptin band (part of AP-1 Golgi adaptor complex)
that runs slightly slower than β2 adaptin. CALM has two splice
variants, 66 and 72 kD. The full-length Eps15R (a doublet of ˜130
kD) and several truncated spliced forms of 100 kD and ˜70 kD were
detected in Eps15R immunoprecipitates (shown by arrows). The cells were
lysed 3 days after transfection. Equal amounts of lysates were resolved
by electrophoresis and blotted with the antibody specific to a targeted
protein (GFP antibody for YFP fusion proteins) and the antibody specific
to unrelated proteins PP1 phosphatase or α-actinin, and TSG101. The
amount of protein in each specific band was normalized to the amount of
non-specific proteins in each lane of the gel. Nearly all of them appear
to be functional, which establishes that Formula VIII and IX can be used
to predict siRNAs' functionality in general in a genome wide manner.

[0447]To generate the fusion of yellow fluorescent protein (YFP) with
Rab5b or Rab5c (YFP-Rab5b or YFP-Rab5c), a DNA fragment encoding the
full-length human Rab5b or Rab5c was obtained by PCR using Pfu polymerase
(Stratagene) with a SacI restriction site introduced into the 5' end and
a KpnI site into the 3' end and cloned into pEYFP-C1 vector (CLONTECH,
Palo Alto, Calif., USA). GFP-CALM and YFP-Rab5a were described previously
(Tebar, Bohlander, & Sorkin (1999) Clathrin Assembly Lymphoid Myeloid
Leukemia (CALM) Protein: Localization in Endocytic-coated Pits,
Interactions with Clathrin, and the Impact of Overexpression on
Clathrin-mediated Traffic, Mol. Biol. Cell 10:2687).

[0448]A number of genes have been identified as playing potentially
important roles in disease etiology. Expression profiles of normal and
diseased kidneys has implicated Edg5 in immunoglobulin A neuropathy, a
common renal glomerular disease. Myc1, MEK1/2 and other related kinases
have been associated with one or more cancers, while lamins have been
implicated in muscular dystrophy and other diseases. For these reasons,
siRNA directed against the genes encoding these classes of molecules
would be important research and therapeutic tools.

[0449]FIG. 12 illustrates four siRNAs targeting 10 different genes (Table
V for sequence and accession number information) that were selected
according to the Formula VIII and assayed as individuals and pools in
HEK293 cells. The level of siRNA induced silencing was measured using the
B-DNA assay. These studies demonstrated that thirty-six out of the forty
individual SMART-selected siRNA tested are functional (90%) and all 10
pools are fully functional.

Example V

Validation of the Algorithm Using Bcl2

[0450]Bcl-2 is a ˜25 kD, 205-239 amino acid, anti-apoptotic protein
that contains considerable homology with other members of the BCL family
including BCLX, MCL1, BAX, BAD, and BIK. The protein exists in at least
two forms (Bcl2a, which has a hydrophobic tail for membrane anchorage,
and Bcl2b, which lacks the hydrophobic tail) and is predominantly
localized to the mitochondrial membrane. While Bcl2 expression is widely
distributed, particular interest has focused on the expression of this
molecule in B and T cells. Bcl2 expression is down-regulated in normal
germinal center B cells yet in a high percentage of follicular lymphomas,
Bcl2 expression has been observed to be elevated. Cytological studies
have identified a common translocation ((14;18)(q32;q32)) amongst a high
percentage (>70%) of these lymphomas. This genetic lesion places the
Bcl2 gene in juxtaposition to immunoglobulin heavy chain gene (IgH)
encoding sequences and is believed to enforce inappropriate levels of
gene expression, and resistance to programmed cell death in the follicle
center B cells. In other cases, hypomethylation of the Bcl2 promoter
leads to enhanced expression and again, inhibition of apoptosis. In
addition to cancer, dysregulated expression of Bcl-2 has been correlated
with multiple sclerosis and various neurological diseases.

[0451]The correlation between Bcl-2 translocation and cancer makes this
gene an attractive target for RNAi. Identification of siRNA directed
against the bcl2 transcript (or Bcl2-IgH fusions) would further our
understanding Bcl2 gene function and possibly provide a future
therapeutic agent to battle diseases that result from altered expression
or function of this gene.

In Silico Identification of Functional siRNA

[0452]To identify functional and hyperfunctional siRNA against the Bcl2
gene, the sequence for Bcl-2 was downloaded from the NCBI Unigene
database and analyzed using the Formula VIII algorithm. As a result of
these procedures, both the sequence and SMARTSCORES®, or siRNA
rankings of the Bcl2 siRNA were obtained and ranked according to their
functionality. Subsequently, these sequences were BLAST'ed (database) to
insure that the selected sequences were specific and contained minimal
overlap with unrelated genes. The SMARTSCORES®, or siRNA rankings for
the top 10 Bcl-2 siRNA are identified in FIG. 13.

In Vivo Testing of Bcl-2 siRNA

[0453]Bcl-2 siRNAs having the top ten SMARTSCORES®, or siRNA rankings
were selected and tested in a functional assay to determine silencing
efficiency. To accomplish this, each of the ten duplexes were synthesized
using 2'-O-ACE chemistry and transfected at 100 nM concentrations into
cells. Twenty-four hours later assays were performed on cell extracts to
assess the degree of target silencing. Controls used in these experiments
included mock transfected cells, and cells that were transfected with a
non-specific siRNA duplex.

[0454]The results of these experiments are presented below (and in FIG.
14) and show that all ten of the selected siRNA induce 80% or better
silencing of the Bcl2 message at 100 nM concentrations. These data verify
that the algorithm successfully identified functional Bcl2 siRNA and
provide a set of functional agents that can be used in experimental and
therapeutic environments.

[0455]Sequences of the siRNAs selected using Formulas (Algorithms) VIII
and IX with their corresponding ranking, which have been evaluated for
the silencing activity in vivo in the present study (Formula VIII and IX,
respectively) are shown in Table V. It should be noted that the "t"
residues in Table V, and elsewhere, when referring to siRNA, should be
replaced by "u" residues.

[0456]Many of the genes to which the described siRNA are directed play
critical roles in disease etiology. For this reason, the siRNAs listed in
the sequence listing may potentially act as therapeutic agents. A number
of prophetic examples follow and should be understood in view of the
siRNA that are identified in the sequence listing. To isolate these
siRNAs, the appropriate message sequence for each gene is analyzed using
one of the before mentioned formulas (preferably formula VIII) to
identify potential siRNA targets. Subsequently these targets are BLAST'ed
to eliminate homology with potential off-targets.

Example VII

Evidence for the Benefits of Pooling

[0457]Evidence for the benefits of pooling have been demonstrated using
the reporter gene, luciferase. Ninety siRNA duplexes were synthesized
using Dharmacon proprietary ACE® chemistry against one of the
standard reporter genes: firefly luciferase. The duplexes were designed
to start two base pairs apart and to cover approximately 180 base pairs
of the luciferase gene (see sequences in Table III). Subsequently, the
siRNA duplexes were co-transfected with a luciferase expression reporter
plasmid into HEK293 cells using standard transfection protocols and
luciferase activity was assayed at 24 and 48 hours.

[0458]Transfection of individual siRNAs showed standard distribution of
inhibitory effect. Some duplexes were active, while others were not. FIG.
15 represents a typical screen of ninety siRNA duplexes (SEQ. ID NO.
0032-0120) positioned two base pairs apart. As the figure suggests, the
functionality of the siRNA duplex is determined more by a particular
sequence of the oligonucleotide than by the relative oligonucleotide
position within a gene or excessively sensitive part of the mRNA, which
is important for traditional anti-sense technology.

[0459]When two continuous oligonucleotides were pooled together, a
significant increase in gene silencing activity was observed (see FIGS.
16A and B). A gradual increase in efficacy and the frequency of pools
functionality was observed when the number of siRNAs increased to 3 and 4
(FIGS. 16A, 16B, 17A, and 17B). Further, the relative positioning of the
oligonucleotides within a pool did not determine whether a particular
pool was functional (see FIGS. 18A and 18B, in which 100% of pools of
oligonucleotides distanced by 2, 10 and 20 base pairs were functional).

[0460]However, relative positioning may nonetheless have an impact. An
increased functionality may exist when the siRNA are positioned
continuously head to toe (5' end of one directly adjacent to the 3' end
of the others).

[0461]Additionally, siRNA pools that were tested performed at least as
well as the best oligonucleotide in the pool, under the experimental
conditions whose results are depicted in FIG. 19. Moreover, when
previously identified non-functional and marginally (semi) functional
siRNA duplexes were pooled together in groups of five at a time, a
significant functional cooperative action was observed (see FIG. 20). In
fact, pools of semi-active oligonucleotides were 5 to 25 times more
functional than the most potent oligonucleotide in the pool. Therefore,
pooling several siRNA duplexes together does not interfere with the
functionality of the most potent siRNAs within a pool, and pooling
provides an unexpected significant increase in overall functionality

Example VIII

Additional Evidence of the Benefits of Pooling

[0462]Experiments were performed on the following genes:
β-galactosidase, Renilla luciferase, and Secreted alkaline
phosphatase, which demonstrates the benefits of pooling. (see FIGS. 21A,
21B and 21C). Individual and pools of siRNA (described in Figure legends
21A-C) were transfected into cells and tested for silencing efficiency.
Approximately 50% of individual siRNAs designed to silence the
above-specified genes were functional, while 100% of the pools that
contain the same siRNA duplexes were functional.

Example IX

Highly Functional siRNA

[0463]Pools of five siRNAs in which each two siRNAs overlap to 10-90%
resulted in 98% functional entities (>80% silencing). Pools of siRNAs
distributed throughout the mRNA that were evenly spaced, covering an
approximate 20-2000 base pair range, were also functional. When the pools
of siRNA were positioned continuously head to tail relative to mRNA
sequences and mimicked the natural products of Dicer cleaved long double
stranded RNA, 98% of the pools evidenced highly functional activity
(>95% silencing).

Example X

Human Cyclophilin B

[0464]Table III above lists the siRNA sequences for the human cyclophilin
B protein. A particularly functional siRNA may be selected by applying
these sequences to any of Formula I to VII above.

[0465]Alternatively, one could pool 2, 3, 4, 5 or more of these sequences
to create a kit for silencing a gene. Preferably, within the kit there
would be at least one sequence that has a relatively high predicted
functionality when any of Formulas I-VII is applied.

Example XI

Sample Pools of siRNAs and Their Application to Human Disease

[0466]The genetic basis behind human disease is well documented and siRNA
may be used as both research or diagnostic tools and therapeutic agents,
either individually or in pools. Genes involved in signal transduction,
the immune response, apoptosis, DNA repair, cell cycle control, and a
variety of other physiological functions have clinical relevance and
therapeutic agents that can modulate expression of these genes may
alleviate some or all of the associated symptoms. In some instances,
these genes can be described as a member of a family or class of genes
and siRNA (randomly, conventionally, or rationally designed) can be
directed against one or multiple members of the family to induce a
desired result.

[0467]To identify rationally designed siRNA to each gene, the sequence was
analyzed using Formula VIII or Formula X to identify rationally designed
siRNA. To confirm the activity of these sequences, the siRNA are
introduced into a cell type of choice (e.g., HeLa cells, HEK293 cells)
and the levels of the appropriate message are analyzed using one of
several art proven techniques. siRNA having heightened levels of potency
can be identified by testing each of the before mentioned duplexes at
increasingly limiting concentrations. Similarly, siRNA having increased
levels of longevity can be identified by introducing each duplex into
cells and testing functionality at 24, 48, 72, 96, 120, 144, 168, and 192
hours after transfection. Agents that induce >95% silencing at
sub-nanomolar concentrations and/or induce functional levels of silencing
for >96 hours are considered hyperfunctional.

Example XII

Validation of Multigene Knockout Using Rab5 and Eps

[0468]Two or more genes having similar, overlapping functions often leads
to genetic redundancy. Mutations that knockout only one of, e.g., a pair
of such genes (also referred to as homologs) results in little or no
phenotype due to the fact that the remaining intact gene is capable of
fulfilling the role of the disrupted counterpart. To fully understand the
function of such genes in cellular physiology, it is often necessary to
knockout or knockdown both homologs simultaneously. Unfortunately,
concomitant knockdown of two or more genes is frequently difficult to
achieve in higher organisms (e.g., mice) thus it is necessary to
introduce new technologies dissect gene function. One such approach to
knocking down multiple genes simultaneously is by using siRNA. For
example, FIG. 11 showed that rationally designed siRNA directed against a
number of genes involved in the clathrin-mediated endocytosis pathway
resulted in significant levels of protein reduction (e.g., >80%). To
determine the effects of gene knockdown on clathrin-related endocytosis,
internalization assays were performed using epidermal growth factor and
transferrin. Specifically, mouse receptor-grade EGF (Collaborative
Research Inc.) and iron-saturated human transferrin (Sigma) were
iodinated as described previously (Jiang, X., Huang, F., Marusyk, A. &
Sorkin, A. (2003) Mol Biol Cell 14, 858-70). HeLa cells grown in 12-well
dishes were incubated with 125I-EGF (1 ng/ml) or
125I-transferrin (1 μg/ml) in binding medium (DMEM, 0.1% bovine
serum albumin) at 37° C., and the ratio of internalized and
surface radioactivity was determined during 5-min time course to
calculate specific internalization rate constant kc as described
previously (Jiang, X et al.). The measurements of the uptakes of
radiolabeled transferrin and EGF were performed using short time-course
assays to avoid influence of the recycling on the uptake kinetics, and
using low ligand concentration to avoid saturation of the
clathrin-dependent pathway (for EGF Lund, K. A., Opresko, L. K.,
Strarbuck, C., Walsh, B. J. & Wiley, H. S. (1990) J. Biol. Chem. 265,
15713-13723).

[0469]The effects of knocking down Rab5a, 5b, 5c, Eps, or Eps 15R
(individually) are shown in FIG. 22 and demonstrate that disruption of
single genes has little or no effect on EGF or Tfn internalization. In
contrast, simultaneous knock down of Rab5a, 5b, and 5c, or Eps and Eps
15R, leads to a distinct phenotype (note: total concentration of siRNA in
these experiments remained constant with that in experiments in which a
single siRNA was introduced, see FIG. 23). These experiments demonstrate
the effectiveness of using rationally designed siRNA to knockdown
multiple genes and validates the utility of these reagents to override
genetic redundancy.

Example XIII

Validation of Multigene Targeting Using G6PD, GAPDH, PLK, and UQC

[0470]Further demonstration of the ability to knock down expression of
multiple genes using rationally designed siRNA was performed using pools
of siRNA directed against four separate genes. To achieve this, siRNA
were transfected into cells (total siRNA concentration of 100 nM) and
assayed twenty-four hours later by B-DNA. Results shown in FIG. 24 show
that pools of rationally designed molecules are capable of simultaneously
silencing four different genes.

Example XIV

Validation of Multigene Knockouts as Demonstrated by Gene Expression
Profiling, a Prophetic Example

[0471]To further demonstrate the ability to concomitantly knockdown the
expression of multiple gene targets, single siRNA or siRNA pools directed
against a collection of genes (e.g., 4, 8, 16, or 23 different targets)
are simultaneously transfected into cells and cultured for twenty-four
hours. Subsequently, mRNA is harvested from treated (and untreated) cells
and labeled with one of two fluorescent probes dyes (e.g., a red
fluorescent probe for the treated cells, a green fluorescent probe for
the control cells.). Equivalent amounts of labeled RNA from each sample
is then mixed together and hybridized to sequences that have been linked
to a solid support (e.g., a slide, "DNA CHIP"). Following hybridization,
the slides are washed and analyzed to assess changes in the levels of
target genes induced by siRNA.

Example XV

Identifying Hyperfunctional siRNA

[0472]Identification of Hyperfunctional Bcl-2 siRNA

[0473]The ten rationally designed Bcl2 siRNA (identified in FIG. 13, 14)
were tested to identify hyperpotent reagents. To accomplish this, each of
the ten Bcl-2 siRNA were individually transfected into cells at a 300 pM
(0.3 nM) concentrations. Twenty-four hours later, transcript levels were
assessed by B-DNA assays and compared with relevant controls. As shown in
FIG. 25, while the majority of Bcl-2 siRNA failed to induce functional
levels of silencing at this concentration, siRNA 1 and 8 induced >80%
silencing, and siRNA 6 exhibited greater than 90% silencing at this
subnanomolar concentration.

[0474]By way of prophetic examples, similar assays could be performed with
any of the groups of rationally designed genes described in the Examples.
Thus for instance, rationally designed siRNA sequences directed against a
gene of interest could be introduced into cells at increasingly limiting
concentrations to determine whether any of the duplexes are
hyperfunctional.

Example XVI

Gene Silencing: Prophetic Example

[0475]Below is an example of how one might transfect a cell.

[0476]Select a cell line. The selection of a cell line is usually
determined by the desired application. The most important feature to RNAi
is the level of expression of the gene of interest. It is highly
recommended to use cell lines for which siRNA transfection conditions
have been specified and validated.

[0477]Plate the cells. Approximately 24 hours prior to transfection, plate
the cells at the appropriate density so that they will be approximately
70-90% confluent, or approximately 1×105 cells/ml at the time
of transfection. Cell densities that are too low may lead to toxicity due
to excess exposure and uptake of transfection reagent-siRNA complexes.
Cell densities that are too high may lead to low transfection
efficiencies and little or no silencing. Incubate the cells overnight.
Standard incubation conditions for mammalian cells are 37° C. in
5% CO2. Other cell types, such as insect cells, require different
temperatures and CO2 concentrations that are readily ascertainable
by persons skilled in the art. Use conditions appropriate for the cell
type of interest.

[0478]siRNA re-suspension. Add 20 μl siRNA universal buffer to each
siRNA to generate a final concentration of 50 μM.

[0479]siRNA-lipid complex formation. Use RNase-free solutions and tubes.
Using the following table, Table VI:

[0480]Transfection. Create a Mixture 1 by combining the specified amounts
of OPTI-MEM serum free media and transfection reagent in a sterile
polystyrene tube. Create a Mixture 2 by combining specified amounts of
each siRNA with OPTI-MEM media in sterile 1 ml tubes. Create a Mixture 3
by combining specified amounts of Mixture 1 and Mixture 2. Mix gently (do
not vortex) and incubate at room temperature for 20 minutes. Create a
Mixture 4 by combining specified amounts of Mixture 3 to complete media.
Add appropriate volume to each cell culture well. Incubate cells with
transfection reagent mixture for 24-72 hours at 37° C. This
incubation time is flexible. The ratio of silencing will remain
consistent at any point in the time period. Assay for gene silencing
using an appropriate detection method such as RT-PCR, Western blot
analysis, immunohistochemistry, phenotypic analysis, mass spectrometry,
fluorescence, radioactive decay, or any other method that is now known or
that comes to be known to persons skilled in the art and that from
reading this disclosure would useful with the present invention. The
optimal window for observing a knockdown phenotype is related to the mRNA
turnover of the gene of interest, although 24-72 hours is standard. Final
Volume reflects amount needed in each well for the desired cell culture
format. When adjusting volumes for a Stock Mix, an additional 10% should
be used to accommodate variability in pipetting, etc. Duplicate or
triplicate assays should be carried out when possible.

Example XVII

siRNAs That Target BACE

[0481]siRNAs that target nucleotide sequences for BACE (including NCBI
accession numbers NM--138971, NM--138972, NM--138973,
NM--012105, NM--138991, NM--138992 and NM--012104)
and having sequences generated in silico by the algorithms herein, are
provided. In various embodiments, the siRNAs are rationally designed. In
various embodiments, the siRNAs are functional or hyperfunctional. These
siRNA that have been generated by the algorithms of the present invention
include:

[0482]Thus, consistent with Example XVII, the present invention provides
an siRNA that targets a nucleotide sequence for BACE, wherein the siRNA
is selected from the group consisting of SEQ. ID NOs. 438-734.

[0483]In another embodiment, an siRNA is provided, said siRNA comprising a
sense region and an antisense region, wherein said sense region and said
antisense region are at least 90% complementary, said sense region and
said antisense region together form a duplex region comprising 18-30 base
pairs, and said sense region comprises a sequence that is at least 90%
similar to a sequence selected from the group consisting of: SEQ. ID NOs
438-734.

[0484]In another embodiment, an siRNA is provided wherein the siRNA
comprises a sense region and an antisense region, wherein said sense
region and said antisense region are at least 90% complementary, said
sense region and said antisense region together form a duplex region
comprising 18-30 base pairs, and said sense region comprises a sequence
that is identical to a contiguous stretch of at least 18 bases of a
sequence selected from the group consisting of: SEQ. ID NOs 438-734.

[0485]In another embodiment, an siRNA is provided wherein the siRNA
comprises a sense region and an antisense region, wherein said sense
region and said antisense region are at least 90% complementary, said
sense region and said antisense region together form a duplex region
comprising 19-30 base pairs, and said sense region comprises a sequence
that is identical to a contiguous stretch of at least 18 bases of a
sequence selected from the group consisting of: SEQ. ID NOs 438-734.

[0486]In another embodiment, a pool of at least two siRNAs is provided,
wherein said pool comprises a first siRNA and a second siRNA, said first
siRNA comprises a duplex region of length 18-30 base pairs that has a
first sense region that is at least 90% similar to 18 bases of a first
sequence selected from the group consisting of: SEQ. ID NOs 438-734 and
said second siRNA comprises a duplex region of length 18-30 base pairs
that has a second sense region that is at least 90% similar to 18 bases
of a second sequence selected from the group consisting of: SEQ. ID NOs
438-734 and wherein said first sense region and said second sense region
are not identical.

[0487]In another embodiment, a pool of at least two siRNAs is provided,
wherein said pool comprises a first siRNA and a second siRNA, said first
siRNA comprises a duplex region of length 18-30 base pairs that has a
first sense region that is identical to at least 18 bases of a sequence
selected from the group consisting of: SEQ. ID NOs 438-734 and wherein
the second siRNA comprises a second sense region that comprises a
sequence that is identical to at least 18 bases of a sequence selected
from the group consisting of: SEQ. ID NOs 438-734.

[0488]In another embodiment, a pool of at least two siRNAs is provided,
wherein said pool comprises a first siRNA and a second siRNA, said first
siRNA comprises a duplex region of length 19-30 base pairs and has a
first sense region comprising a sequence that is at least 90% similar to
a sequence selected from the group consisting of: SEQ. ID NOs 438-734,
and said duplex of said second siRNA is 19-30 base pairs and comprises a
second sense region that comprises a sequence that is at least 90%
similar to a sequence selected from the group consisting of: SEQ. ID NOs
438-734.

[0489]In another embodiment, a pool of at least two siRNAs is provided,
wherein said pool comprises a first siRNA and a second siRNA, said first
siRNA comprises a duplex region of length 19-30 base pairs and has a
first sense region comprising a sequence that is identical to at least 18
bases of a sequence selected the group consisting of: SEQ. ID NOs 438-734
and said duplex of said second siRNA is 19-30 base pairs and comprises a
second sense region comprising a sequence that is identical to a sequence
selected from the group consisting of: SEQ. ID NOs 438-734.

[0490]In each of the aforementioned embodiments, preferably the antisense
region is at least 90% complementary to a contiguous stretch of bases of
one of the NCBI sequences identified in Example XVII; each of the recited
NCBI sequences is incorporated by reference as if set forth fully herein.
In some embodiments, the antisense region is 100% complementary to a
contiguous stretch of bases of one of the NCBI sequences identified in
Example XVII.

[0491]Further, in some embodiments that are directed to siRNA duplexes in
which the antisense region is 20-30 bases in length, preferably there is
a stretch of 19 bases that is at least 90%, more preferably 100%
complementary to the recited sequence id number and the entire antisense
region is at least 90% and more preferably 100% complementary to a
contiguous stretch of bases of one of the NCBI sequences identified in
Example XVII.

[0492]While the invention has been described in connection with specific
embodiments thereof, it will be understood that it is capable of further
modifications and this application is intended to cover any variations,
uses, or adaptations of the invention following, in general, the
principles of the invention and including such departure from the present
disclosure as come within known or customary practice within the art to
which the invention pertains and as may be applied to the essential
features hereinbefore set forth and as follows in the scope of the
appended claims.